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<h1>Chapter 6: Exercise 11</h1>
<h2>a</h2>
<pre><code class="r">set.seed(1)
library(MASS)
library(leaps)
library(glmnet)
</code></pre>
<pre><code>## Loading required package: Matrix Loading required package: lattice Loaded
## glmnet 1.9-5
</code></pre>
<h3>Best subset selection</h3>
<pre><code class="r">predict.regsubsets = function(object, newdata, id, ...) {
form = as.formula(object$call[[2]])
mat = model.matrix(form, newdata)
coefi = coef(object, id = id)
mat[, names(coefi)] %*% coefi
}
k = 10
p = ncol(Boston) - 1
folds = sample(rep(1:k, length = nrow(Boston)))
cv.errors = matrix(NA, k, p)
for (i in 1:k) {
best.fit = regsubsets(crim ~ ., data = Boston[folds != i, ], nvmax = p)
for (j in 1:p) {
pred = predict(best.fit, Boston[folds == i, ], id = j)
cv.errors[i, j] = mean((Boston$crim[folds == i] - pred)^2)
}
}
rmse.cv = sqrt(apply(cv.errors, 2, mean))
plot(rmse.cv, pch = 19, type = "b")
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-2"/> </p>
<pre><code class="r">which.min(rmse.cv)
</code></pre>
<pre><code>## [1] 9
</code></pre>
<pre><code class="r">rmse.cv[which.min(rmse.cv)]
</code></pre>
<pre><code>## [1] 6.593
</code></pre>
<h3>Lasso</h3>
<pre><code class="r">x = model.matrix(crim ~ . - 1, data = Boston)
y = Boston$crim
cv.lasso = cv.glmnet(x, y, type.measure = "mse")
plot(cv.lasso)
</code></pre>
<p><img 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EiABGpKYFFNb7TqfRzBW7Xn2W4SIAESIIGUJkADn9Ldy8ZFgQB98FGAyCxIIAoE6IM3CJEG3iAwJrccAfrgLdflbLBJCdAHb7Bj6IM3CIzJLUeAPnjLdTkbbFIC9MEb7BiO4A0CY3ISIAESIAESSAYCNPDJ0EusYyIJ0AefSPosmwT2EKAPfg+LiGJmNPDiNtgvotozEQnEngB98LFnzBJIIBIC9MFHQkmXxiwG3oU6jYKshngg2yCFEPG59IUwkECiCIgPfmOiCme5JEACFQTEHsysOGOkWgJmechuHGraHNIbsgwixl12LDoYMgaSAZkIYSABEiABEiCBmBLIy8sbbrPZWusK6Y74Qt35z9nZ2ZN156aMmsXAnw06PSAbdJR2Iv4z5HbIgxAaeEBgiDsB8cEvgMisEgMJkEDiCIgPXgZ+MX8rG4z7ez6fr47WVLvd/grO9S8q265d47F6Ap8gydVVJHsE+jeruGZEfRUS9zdyA9OSAAjIa4abkQQJkEDCCXRDDU5JRC3y8/O/q0W5z+DeI2txf41vNcsIfiRaINMdQyFLIbsgDSBdIVLH8yCRhM5I1LGKhCdCX1zFNapJoCoCXAdfFRnqSSC+BLgO3iBvsxj4eaj3ERCZphcjfQBkNkSm5eWhCj8kkiB+/EOrSCivGRTfPgMJkAAJkAAJpDwBsxh4B0g/BOkDaQVxQ0ogqyD3QmQKP5IgPwZEQoUWUHKqNRQZ6sIRoA8+HB1eI4H4EeiAouLig49fk2JbklkM/GNoZhPIWZD9ILmQ+yE+yHMQeYr+XQgDCcSbANfBx5s4yyOB0AS4Dj40lyq1ZjHw56OGMj2/M1jTsTgOglwP6Qd5BEIDDwgMcSdAH3zckbNAEghJgD74kFiqVtqrvhTXK3+iNJkK1cLxiMimNxLEH68Z/oCC/5EACZAACZAACYQnYJYRvGxmI352WfOeDukEkWUFvSF5kMshDCSQCAL0wSeCOsskgX0J0Ae/L5OwGrMY+FmoZUvIhZAiyFcQb1DkqXoubwMEhoQQoA8+IdhZKAnsQ4A++H2QhFeYxcBLLeWp+XcqVZd7gFcCwtO4E6APPu7IWSAJhCRAH3xILFUrzeKDr7qGvEICJEACJEACJGCYAA28YWS8wWIExAcv0/QMJEACiSUgPnjZsIwhQgI08BGCYjLLEqAP3rJdz4abjAB98AY7xEw+eINVZ3ISiAsB+uDjgpmFkEC1BOiDrxbR3gk4gt+bB89IgARIgARIICUI0MCnRDeyETEkQB98DOEyaxIwQIA+eAOwJCkNvEFgTG45AvTBW67L2WCTEqAP3mDH0AdvEBiTW44AffCW63I22KQE6IM32DEcwRsExuQkQAIkQAIkkAwEaOCToZdYx0QSoA8+kfRZNgnsIUAf/B4WEcVo4CPCxEQWJkAfvIU7n003FQH64A12B33wBoExueUI0AdvuS5ng01KgD54gx1DA28QGJOTAAmQAAmkDoG8vLyJaE0zaZENAYfOfr//HzkPBnmVeVIGGvik7DZWOo4ExAe/ALItjmWyKBIggX0JiA8+CzJ/30s113g8nuFpaWkOyQFxV0ZGxls+n6+flmMJQmZm5g3aeTIdaeCTqbdY10QQoA8+EdRZJgnsSyAmPvjBgwfv0ooaO3ZsOuKlAwcO3K7p5Jifn68/TZo4DXzSdBUrmiAC9MEnCDyLJYFKBOiDrwSkulM+RV8dIV4nARIgARIggSQkQAOfhJ3GKseVANfBxxU3CyOBKgmID57vg68Sz74XaOD3ZUINCegJ0Aevp8E4CSSOQEx88IlrTuxLpg8+9oxZQnIToA8+ufuPtU8dAvTBG+xLjuANAmNyEiABEiABEkgGAjTwydBLrGMiCdAHn0j6LJsE9hCgD34Pi4hiNPARYWIiCxOgD97Cnc+mm4oAffAGu4M+eIPAmNxyBOiDt1yXs8EmJUAfvMGO4QjeIDAmJwESIAESIIFkIEADnwy9xDomkgB98Imkz7JJYA8B+uD3sIgoRgMfESYmsjAB+uAt3PlsuqkI0AdvsDvogzcIjMktR4A+eMt1ORtsUgL0wRvsGI7gDQJjchIgARIgARJIBgI08MnQS6xjIgnQB59I+iybBPYQoA9+D4uIYjTwEWFiIgsToA/ewp3PppuKAH3wBruDPniDwJjccgTog7dcl7PBJiVAH7zBjuEI3iAwJicBEiABEiCBZCBAA58MvcQ6JpIAffCJpM+ySWAPAfrg97CIKEYDHxEmJrIwAfrgLdz5bLqpCNAHb7A76IM3CIzJLUeAPnjLdTkbbFIC9MEb7BiO4A0CY3ISIAESIAESSAYCHMEnQy+xjokkID74BZBtiawEyyYBElDig8+CzK8pi/z8/Dtwr0z1K7/fnwbpbLfb/9LyKysr+1mLp8KRBj4VepFtiCUB+uBjSZd5k0DkBKLhg//V5/O5pEgY9iybzXYqzl/UVWGtLp70URr4pO9CNiDGBOiDjzFgZk8CERKotQ8+Ozv7R60sjOYbYwR/zYABA6ZrurFjx6a7XAH7r6mS+kgffFJ3HytPAiRAAiRAAqEJ0MCH5kItCWgEuA5eI8EjCSSWgPjgD09sFZKrdDMaeHEb7JdcGFnbFCZAH3wKdy6bllQEouGDT6oG17ayZjHw4vQYBVkN8UDkieVCiPhc+kIYSCBRBMQHvzFRhbNcEiCBCgJiD2ZWnDFSLQGzPGQ3DjVtDukNWQYR4y7LIQ6GjIFkQCZCGEiABEiABEiABCIgYJYR/NmoazZkIWQ3xA/ZCZE1ibdDLoYwkEAiCNAHnwjqLJME9iXQASr64PflUqXGLAZepl7kizRUOB/KzaEuUEcCcSBAH3wcILMIEoiAAH3wEUDSJzHLFP1IVGoyZChkKWQXpAGkK0TqeB4kkiDT/E2qSNgIevH1M5CAEQJcB2+EFtOSQOwIyECQwQABsxj4eajzEZAekHYQMdRbIJMgX0Fkyj6ScAwSnVVFwm7Qb63iGtUkQAIkQAIkkFIEzGLg5YG6WyCnQp6FiCF+GZIOmQLJgYhvvrrwCRKIhAqjoWwW6gJ1JBCGgLiOFkBkZQcDCZBA4giID15sxfzEVSG5SjaLD/5uYDsW8jnkOcjjkAsh7SAyrX4FhIEEEkGAPvhEUGeZJLAvAfrg92USVmOWEfxFqKUYeFkeJ6PsxhDtrT6PIS6j+lchDCQQbwL0wcebOMsjgdAE6IMPzaVKrVlG8P9DDcV3Lg/WnQI5CqKF7oj8rp3wSAIkQAIkQAIkUD0Bs4zgn0FVX4GIj2UspD5EjL74Pk+C9IQwkEAiCNAHnwjqLJME9iUg9iELQh/8vmxCasxi4GU6XnatE3+nPGAnD9f1gjSE9IUUQxhIIBEE6INPBHWWSQL7EqAPfl8mYTVmMfBSSVkKJ8ZdghvycSDG/0ggsQTeT2zxLJ0ESCBIgD54g38KZvHBG6w2k5MACZAACZAACYQjQAMfjg6vkUD5FsoyTc9AAiSQWALig+de9Ab6wExT9AaqzaQkEDcC9MHHDTULIoGwBAz54PPy8m5Hbg7J0WazyRtJ2/r9/n/lXALi8hB3Sgca+JTuXjYuCgTog48CRGZBAlEgYMgHD6O+BEZcm6VuhnhP1OEzXT126uIpGaWBT8luZaNIgARIwNoEsrOzK4z5hAkTOjgcjh7QVWxlnp+f3xhGP6Uhab9uUrqRbBwJ1IKArIOnD74WAHkrCUSJAH3wBkHSwBsExuSWI0AfvOW6nA02KQFDPniTtiGu1eIUfVxxs7AkJEAffBJ2GquckgQM+eBTkoDBRnEEbxAYk5MACZAACZBAMhCggU+GXmIdE0mAPvhE0mfZJLCHAH3we1hEFKOBjwgTE1mYAH3wFu58Nt1UBOiDN9gd9MEbBMbkliNAH7zlupwNNikB+uANdgxH8AaBMTkJkAAJkAAJJAMBGvhk6CXWMZEE6INPJH2WTQJ7CNAHv4dFRDEa+IgwMZGFCdAHb+HOZ9NNRYA+eIPdQR+8QWBMbjkC9MFbrsvZYJMSoA/eYMdwBG8QGJOTAAmQAAmQQDIQoIFPhl5iHRNJgD74RNJn2SSwhwB98HtYRBSjgY8IExNZmAB98BbufDbdVATogzfYHfTBGwTG5JYjQB+85bqcDTYpAfrgDXYMDbxBYExOAiRAAiRgHgK5ublpLVq0+Farkc1mq4P3vDfB+SpNh+OburhlojTwlulqNrSGBMQHvwCyrYb38zYSIIHoEBAffBZkvj47GPhSnPfUdHl5eYch3rd///5DNN2ECRM6OByOHtq5VY70wVulp9nOmhKgD76m5HgfCUSXAH3wBnlyBG8QGJNbjgB98JbrcjbYpATogzfYMRzBGwTG5CRAAiRAAiSQDARo4JOhl1jHRBLgOvhE0mfZJLCHQAdED99zGp9YiUrrdcQnX7QsUapTfEqMXik08NFjyZxSkwB98KnZr2xV8hGIuw/eo5y3OJT9g8M//aJTmkqfifPjkwkbffDJ1FusayII0AefCOoskwT2JZAAH7x9OKpR14b//Eq1wKEv5BdIUgSO4JOim1hJEiABEiCB+BPwz4Zp95WX6/fg6I1/HWpeIg18zdnxTmsQoA/eGv3MVpqfQNx98IXK0x9YdhdlZZVgBD/lQ+W93fyY9tSQBn4PC8ZIIBQB+uBDUaGOBOJPIO4++P2U2uFUngZTnnrkV5fy3HClUmXxb3bNS6QPvubseKc1CNAHb41+ZivNTyABPnjzQwlXQ47gw9HhNRIgARIgARJIUgI08Enacax23AjQBx831CyIBMISiLsPPmxtkuAip+iToJNYxYQSoA8+ofhZOAlUEBAffMP8/PyDNA3eGpeOl8jU8fl8OzRdaWlpJnTaqaWPNPCW7n42PgIC9MFHAIlJSCAOBBY99dRTmTDqT2tl4dWwzWHc20CH5WzlAboftLjVjzTwVv8LYPtJgARIIEkIDBs2rBBVHaBVF6P5k2Dce+HVsPdruuDrYo/Vzq18pA/eyr3PtkdCgD74SCgxDQnEngB98AYZ08AbBMbkliNAH7zlupwNNimBuK+DNymHiKvFKfqIUTGhRQnQB2/RjmezTUeA6+ANdglH8AaBMTkJkAAJkAAJJAMBGvhk6CXWMZEE6INPJH2WTQJ7CNAHv4dFRDEzGnhxG2ALYAYSMAUB+uBN0Q2sBAko+uAN/hGYxcC7UO9RkNUQeSXfNogshxCfS18IAwkkioD44DcmqnCWSwIkUEFA7MHMijNGqiVglofsxqGmzSG9IcsgYtyzIAdDxkAyIBMhDCRAAiRAAiRAAhEQMMsI/mzUNRuyELIbglfvqp2QnyHy/t2LIQwkkAgC9MEngjrLJIF9CXSA6vB91dRURcAsBl6mXuSLNFQ4H8rNoS5QRwJxIEAffBwgswgSiIAAffARQNInMcsU/UhUajJkKGQpZBekAaQrROp4HiSSUAeJREKFdCj5BoJQZKgLR4Dr4MPR4TUSiBGB8ePHN09LS5uiy74BtqWtg73mN+h0b+vijFYiYBYDLw8xHQU5DtIOIv54GbWL310eqpAp+0jCZUh0SRUJD4V+bRXXqCYBEiABEjARgUGDBokh76lVCXvMnwfjfkh2dvZTmk72oke8tXbO494EzGLgP0O1iiDXQWbsXUVDZ28itUioMBrKZqEuUEcCYQiI62gBRFZ2MJAACSSIwOzZs5vb7fYWsSoeBqh12uBhX3nq1unYT7lm/6s8Jx5SvqorVkXGPN9wPviqprpjVak/kPFPkByITM8zkIAZCNAHb4ZeYB0sT2D37t3pBQUFsqIqJsGl0ufZsHIrvahY3LndOirngJgUFMdMwxl4WZd+dxzr8iLKkumWcyFrIHnBc1kux0ACiSLAdfCJIs9ySUBH4LTTTlsJWa5TRTXqV36xO1pIT1Oqk3aSrMdwBn4lGiV+63g+mLYE5Z0FOQYiy+XegGyHiPFnIAESIAESIIGYEICBf04yLktLK8XB71bex2JSUBwzDWfgi1EPWaImT7T/DfkzKM/iGOsg5d0JaQ+REfzDEAYSSAQB8cHLND0DCZBAAgmID37OnDkx88G7lHdSSb06p/122YV/lSpP+0yl1iWwuVEpGrMQVYYvcUUeLhID2xSyGuKGbIVEOzyJDCX/UEF2tRNhIIFEEKAPPhHUWSYJVCIgPng8RR8zH7wU9+qoh352uVzrT/nv26sqFZ+Up+EM/Bq0KBdyI2QbpCHkQ0gfSLQD1zJGmyjzixYB8cEzkAAJJJiA+OBh4OtNmTIlwTVJnuLDTdFnoxmdILIffCPIgRA8ZKiGQxhIgARIgARIgARMTCDcCP541Fs2FPhfsP7yEpiHIM8Ez3kgASsQEB8818FboafZxoQRkF3rHA5Hjq4CTRAX+7Re0y1atGiL2+1urp3zWD2BcAZe1qSfDPlYl42cb9adM0oCqU6APvhU72G2L+EEYLh3pqenv6tVBMb+TGxLm+Xz+T7QdNu3bz+xrKwspj54raxUOYYz8AJbNp85FfIj5CiIvMlHzhlIwCoE6IO3Sk+znQkjkJOTI6u2ZmsVwLa0HeBv3w/b1ep1TaBz0gevUar+GM4HL1vHHgp5EyLpPoN0g8yHMJAACZAACZAACZiYQLgRvOxkJy+BedzE9WfVSCDWBOiDjzVh5k8CERCI9V70EVQh6ZKEM/Ar0ZpjIA5IWdK1jBUmgegQoA8+OhyZCwnUikA81sHXqoImvDncFH0id7IzISpWyaIExAcvM1kMJEACCSQQ673oE9i0mBUdbgQvr23tFaLkrSF0VJEACZAACZAACZiIQDgDL6/Kow/eRJ3FqiSEAH3wCcHOQklgbwL0we/NI5KzcAaePvhICDJNqhOgDz7Ve5jtiyuB/Px8WZ01TleofMZ8kB063QdYB+/RnSv64PU0IouHM/B6H7y8CEZ70O4rxHMiy56pSCDpCYgPnoEESCBKBLKzs2V/lZ5adhMnTvyP3W4vhH6ypsM6+KsQ3087lyP3otfTiCwezsBrb5OrnBN98JWJ8JwESIAESIAETEYglIGXl8rIvvMyRS+iDwfgpC1ksV7JOAmkMAH64FO4c9m05CFAH7zxvgq1TO5nZNM4mNWJOL6ky7YH4rfpzhklgVQnQB98qvcw25cUBMQHX1BQwL3oDfRWKAOvv70eTmTEzkACViUgPniug7dq77PdpiHAdfDGuyLUFL3xXHgHCZAACZAACSQJAbxopY1jwJDPylzOA/sp19RHleey3PIn+ZOkBZFVs7oRfGS5MBUJpC4B8cHLND0DCZBAAgmID37OnDktolEFp3L9a/f5DnWWuGXK/+wRynldNPI1Wx5VjeDFB++HNIS4IE0hEhqUH/g/CViGAH3wlulqNjTaBMaOHdvE6XQep+WL97s3w5K4Epzv1HRY7y42plA7r+oY5XXwy1FO12BZGTZlaxeMp9ShKgO/qFIr9T5IeU88AwlYhQDXwVulp9nOqBOAcc+EQe+iZYz4KYhvgfyl6WD0vVo83DG66+B9k/AetSf8dluZ3afWFCv3xHBlJ+u1UAZelsLZwjSoNMw1XiIBEiABEiCBAIEBAwasQOQZDQc2sJGZ4cX9+/f/RNPJRjdaPF5Hpyp9clPzliuW9DjmziOmvn9lfaU2xavseJYTysBXO1USzwqyLBJIMAGug09wB7B4EhAC0V4HP/XBe6fDPXDFCVPfX5GqhEMZ+FRtK9tFAjUhQB98TajxHhKIMoEo++CjXDtzZsen6M3ZL6yVeQhwHbx5+oI1sTABroM33vk08MaZ8Q4SIAESIAESMD2BUFP001FrWR5XVfgGF4ZXdZF6EkgxAvTBp1iHsjnJSSDaPvjkpGCs1qEM/L3IQvTy0pn7IBMgP0EOhgyEzIMwkIBVCNAHb5WeZjtrRQBPyB9ts9mydZm0xUNsO6DbpelwvkyLGz3SB2+UWLkhr3yXvGxGwtWQByBvyAmCGHlZuyg/AKZAGEjACgS4Dt4Kvcw21ppAWVnZ38jkCS0jrHm/DQb9V8hvmi4tLe0inGunho7RXQdvqOikTRxqBK81pgCRdtpJ8NgNR9mkgIEESIAESIAEKggMGjRoN06WaAqsb9+O+FroK3TBdfBaEh5jTCCcgX8FZX8JOQciv8COgnSAnA9hIAGrEKAP3io9zXaamgB98Ma7J5yB/wfZyR7CF0HEH/8m5FPIOggDCViFAH3wVulpttPUBOiDN9494Qy85LYJ8iKkOUSm5rlNLSAwWIoAffCW6m421qwE6IM33jPh1sHLNXmKfiFElsadAfkQ0gTCQAIkQAIkQAIkYGIC4Ubwt6Dep0MuhUyFyPr4CyGifxTCQAJWIEAfvBV6mW00RCA/P783bhim3YQn4ztgOZzM+MqDdoGAt8TN1OLRONIHb5xiOAN/MrJ7GqL53L2Ij4HkQWjgAYHBEgTog7dEN7ORRghkZ2d/hvQigYCn459B5C3ofw+qFJ6iz9Xi0TjSB2+cYjgDvxrZiZH/TpetPHC3XnfOKAmkOgH64FO9h9m+pCBQUx881ns3cQwd/qKyO467SaX9hVfFyo8RS4RwBn40CMyGnAVpAZENcNpBzoQwkAAJkAAJkIDpCWQo11rl9jjLK2rPLVHp/8tQ7s9NX/EoVDCcgd+F/A+GXAVpC/k+KGU4MpCAVQjQB2+VnmY7TU2gpj547Ju32la+h4u0L8OufG1M3dAoVi6cgR+FcjZCHo9iecyKBJKNAH3wydZjrG9UCcC/Lq7ZflqmeJiuHeLr8WCdW3Q4L0O8xnvMSx6RhFr44L9D/mLUMYq3bSpVHtnPxRIhnIFfCQLHQBwQjtot8efARoYgQB98CChUWYcADPjnO3bskFVUgdCwYcNxbrd7dHFxccCo16tXz+9wOB7UrsfqWFMf/Cjl+c/tDZsVbOrY/vR2c3+/pi62z41VHc2WbzgDX4zKyra0MlUvD9xpRv4rxHMgDCRAAiRAAilOAE/GywoqkUDAEjkvDHrh8OHD5X0lgYBRvhY13TFXKV/TUQ+MRZ3rZ2f/8ofpKhjDCoUz8LIP/YIQZW8NoaOKBFKVwGlomHwOtqVqA9kuEkgGAjX1wSdD22JVx3AGXqboRSqHOpUVUT6XOtWHbI9yvsyOBGpCgD74mlDjPUlJYMKECadiSl5+1AYC4l3hX5e3wQVG8DiXmd2EhFr44BNSXzMUGs7AN0YFZd7lQIj44WXr2gzIL5A+kGgGFzLLhVwHaQWxQYogyyGyZvFVCAMJJIIAffCJoM4yE0IAu8+twHvcZ2iFw6CfDAP/Ns4DAy5c9+Kd7p206/E81tQHH886mq2scAZ+KCqL5xECL5sRX/xLENmbXp6uj3YYhwybQ2T7Q3lwoxCSBZFlerJ7nvywmAhhIAESIAESiBGBW2+9da+ZW/jWN3s8np+HDBkiK6oCAT74vlqcR3MTkFF5VaEjLsjoeRJERtXvQaRj74BEO5yNDLMhCyGylzGWLqqdENlc53bIxRAGEkgEgdNQqEzTM5AACSSQgPjg58yZI5uuMURIINwIXpYStIVMg8gUeiOIPGgkumiHRchQvkhlKqhykNmDzZWVPCeBOBGgDz5OoFlMfAlgdD4QU/BXaqViKr4bzv/EuQywFM43aNfMcKQP3ngvhDPwLyM7GUHLAxYfQ2RzADH070KiHUYiw8kQcQssheyCNIB0hUgdz4MwkEAiCNAHnwjqLDPmBPr37z8BhYgEAqbePy8sLLwsJyen4kE6/AiYol1P9JE+eOM9EM7A/4XsukDKIGLo+0N2QN6BRDvMQ4ZHQHpA2kHEHy+jdvG7yysHA78ocawu3IIEVT0AKC6H5dVlwOskQAIkkGoEYLydMN4V3/d4UM5ZWlpasbYd575UazPbUz46roqD+NqvC3GxO3R3hdDXVlWCDGboMpEH6+THRaTGXW59ISgSrxxGQ9GsspLnJFANAXEdLYBwHXw1oHjZvAQw3d4/MzPzXF0Nj01PT/9Nd75CFzdllOvgjXdLxS+6ELdOhU77A7Ah3hJyO+RzSLSD+PUfgYyFrIQ8DrkM4oT8FyKzBx4IAwnEmwB98PEmzvKiTgDT8eOQqUggYET/HXao28v1KVP02nUzHumDN94r4Qz8MmQnog9yfifkO70yCvGHkMcqiDzgcQ9E6tUNkg4RY39/UHBgIIG4EqAPPq64WVhtCcBvfg4eluus5YPRe3ecL9Sdr9PiyXSMxAfvVq6uvsF3/tfm87frp5ylTuUVe2XZEM7Ah4LSHsoGoS7UUncK7j8IIqP0SyCyLG4NRIIYd9lwh4EESIAESKAaAmVlZVuxWY28PyQQEL8FG9R8pp3D2G/V4ql2tCvbX3aP9miBrR/e/T4N737/ItXaGWl7whl4+eVzvS6jOoi3gVyt00Ur+i8ykrJkM53vIDJ1pE0nyTK5xRAGEkgEAfrgE0GdZUZEAKP1A2HQG2qJnU5nW6/XuwoGPTBAwuh9Jwz8lgEDBojLtSJgOr4iniyRSHzwNuVf5le2DsE2uXDeKFnaF4t6hjPwMjUpT89roRQRmaKPxZr0QchXluH1g8iyvKchN0F8ENnR7hQIAwkkggB98ImgzjIjJXAS3pImy4kDAYb9/3A+RTvH8R9dPKmjkfjgfcr/lbLZr0FDM21+VXe7cu/1wyapAdSg8uEMvCwpi9eysqUo62DIWRBZmif++O0QGbnL1JL8uGAggUQQoA8+EdRZ5j4EMOo+GyPyproL8pzSIkjAvw7jvhLG/Vg8PLfXKifcd53unqSNRuKDdynvwBVdui7b1rZ1r85ff34t1lsXJm2Do1DxcAb+DuRf3R/GCUhTFIV6SBayHO7roMg5AwmQAAmQwB4CsqpIHjzWgjyrVOG+hG9drls+fDlk4DeA0PrIrz/faHUY4Qz8LMCRafKXIT9A5NfibRAZ0cyESHCXH/g/CaQsAfrgU7Zrzdsw+NbHwmB30NVQZjb/gU5TyWBoA0br8v1cETBaH1lxkmKRSHzwKdbkWjcnnIG/Hrk/AHkvWMpsHP8HkT+gR4M6Hkgg1QnQB5/qPZzg9j3//PMH6EffmGZvgirl4S1uDqkapt53YlOaNwsKCq7Sqopd6bwtWrS4VDu3wjESH7wVOBhpYzgDvxsZybI4fTgSJ5b2aehhMG4JAvTBW6KbE9dIbBObDQMvRl2CHXI25EuXyyXnYuC/wXXfsGHD9vruTcYn4QMNquF/kfjga5h1yt4WzsDLkrWvIPIrUUbvR0PaQs6BMJAACZAACRgkgKn3D2GstWVtMkJvB1mqZQNj/haut8LOc//RdHKEMR+oP2ecBCIhEM7Ay9r04yDnQ2Qkfw9EfPE+CAMJWIXAaWgo96K3Sm9HsZ0wyrL1a+DBNzz97oLhlpdorYJ4pRicvw6Dfi6M+RVyLmHs2LHpGLlfVn7G//UE6IPX04gsHs7Ayx/mJsgrENll7gCIPMFZDGEgAasQoA/eKj0dYTthuOtqSXft2mXDS1xc2EzmI02HYzqMt2ywskbT4fwtGPnjN2zYcIumgw9dRvLnauc8hidAH3x4PqGuhjLwrZBQ/linQ2Q95c2Q5yAyoq8HOR6yFcJAAlYgQB+8FXo5RBuDhlz84YGAHeMa4AG4/XBybVClsrKyZHlvQxhv+X4MBMQnIdIdI/Mh5Rq8dH3ChA6497jc3NyKPT2Qv3aZxwgI0AcfAaRKSUIZeFl28RtkFER+qY6ByJTRlxAx9MMhe22kgHMGEiABEkhaAhMnTmyFUfj9ugY0RjwDxlrzlys8DLcK55mQN7R0GJmvw7kY84p74Wc/DNfltdoMMSSAJw5beO+672FHWdmhN6q07zNU6bcxLC4ps65s4G1oxQmQGyA7IL2CRzHuEj6BjAjE+B8JWIMAffBJ3M8w3O1guC/WNaE1/N71oDtD08FA+2GoS3Eo0HQ4/wbpvNBVbPuK864YhR8IYy4DnUDAKPwkRGjMgzxiedD74LG7T7pLpa9z7dwVLNI+1aOcJ2EnuwWxrEOy5V3ZwMtTnaLT/OxnIi67AmlBfs1qRDUdjySQygTogzdh72LKW16BWrGiBwa7AwxwXehO1KqLuA0GuhCiqeQ4H2lXQnenpkSy1ohvh+GerOkwCr8K+v3wkpZ/dLqOWpzH+BPQ++DRYc3RqyswIm0XrEkpXjJzIOJRMfDo/2eQV/tg3nI4GLoPtHP8bUzDJkPjtXOzHisb+FJUVADdDHkH8n+QARAJYBl4GcwvgTP+RwLWIEAffIL7GaPki2GQ++mq0Q5fsNtwHti2Fdd8kPUw3DPgJ39bS4c0x0E/Y+DAgd9rOnxJ50C3GMZcZiMDAaP8/+Be7ZRHkxLQ++BhhNaeqPx4Fizw4wx2zNbQq9w/RKvqO3fuzK1fv36FfSwtLc2Ei6ZiHwLM5LijVVYs86logK4QWX8pyzuegrwG+QzSEjINUgJ5GsJAAiRAAlEnAGMu7sG+WsYwxrJd62pImehgtHdDNweGfDSOy0RXVFTkx5fxQ4j+BGP+u+gkwHDLMl+GFCRwGl5Atlp5Tq7fsOlHBY0bN266ZMm1eAI8anvPDx8+vMJdE8QnLz9LuhDKwC9CK9pCsiDadLwch0BmQDwQBhKwCgF8l3AdfG07GyNnmT5toeUTNNzdMXIWvhLEgB8A+QuC2Vf85/dvwGFDcXHx7UOGDKn48saPgBdxrWjQoEG7JZ0E5F8e4f8pS0Dvg5dGtoErOf+Jhx/C30IvzMjI3w1DJQKhDLyWRDPucv4sRHxWNO5Cg8FKBOiDD9PbQV94Yy0JDHYnfOEei3N5klyCF6NuMewyApJBgxjuzUjXHMfXIR+LDmEj0p2PPdYvy8nJ0Z4BEsM9pfwy/7c6Ab0P3uosIm1/OAOvz+N6nNwH0Rt9/XXGSSBVCdAHH+xZjJwfgUHuqnU0DHJXnMtUpuyPIdPnsktbF8gkxGVaXfZRl2n0m3F+ppxLmDZtmu/MM8+chlHXA+Wa8v+R//n6c8ZJQE9A74PX6xmvmkCkBr7qHHiFBEggqQnAV90LBjhTGgGDLU+ed8FDRDJ1HphSx3kxrnfAUaZBbZIO59/gvBn83xfKuQS88cyDB5E+heEWf3hFgOHuhyeOvRUKRGDg9aeMkwAJxIBApAb+NZQtD9gxkIDVCIihk5Ul25Kt4Zg+PxWG2i71xlPATsSbIypbpQZG3Jgmd4uRxrlMiTsgYuDnIt1hOE6UcwkYhc+H7mEY7p4BRfA/GO7TMJ2+Fxfo9EkYJ4GoEajsg49aximcUaQGPjuFGbBpJBCOgKl88DCgThjc07UKB0fe++F4q6bDUTZoyYIuDcfAiBsG+g+ct8H5R1o65CM7VvaD4b5C0wVfdvIRdOM0nRxpuPU0GE8EAfrgjVMPZ+BlU5sJkEMhLl3WXyAuT9QzkIAVCNTKB//ss8/WycjIqHh6HKPm+jCyMoI+QgfPHjTUMlsQCDiXUbV87rqXawLT4jtxrxPXAqPyoF5mFxpAL/tWBAKWkP0Dg37K+vXrczRd06ZN20F3r376HEa7Me7rp6XhkQTMSqBEpR/o/WLazXa3p+MklfYhtqX92qx1NVO9whn4u1DRBpDBkIrlKIjvNSWH85QMmN68EF+kMnoLBHwxd8OXIVS2rKBKlu1kQGR5j5ZuC9IIUxlBNcFRfJXbIfKFXASdTJGKbhfiPkSFa6ugTnbcklUKu3FddtaSqVG3pMWxGOVjVYhSOEreWyUtrgV0iEvF1uGLXY6yxDEQEF+De334Yg/kJ0okXSlHXJMlSYGAJGslUule2XcbqvIyylOqVUgrxihQrqYLpqvID+erUWYa0rZCXDNGq3BfBkSMSuAHo6TDufh+5e+sTjA/eThLziVt/aBuLdJmQRzQyQ9PCbKESnYug9qvPcW9Beey+Yn0STOItFf4O3GUp7kDHBAX7tJPwlpjWIRzSSPHdhC5VxiLoRX/sda+MuiLoJe+0gw3VIFyRBfoYxwlyJPjboi0Rwtrca9smOHUFLhX9jMvRN/O0nRgV4q4jMD1P6a1rVJlj4pAgJE+CWlkmdBjmg5Pnh+G+Cl4sYn8jQUC/p61KI8kkFQEYHAawH/0r2OXtjTd/l+3cp2Yrjx/JVVDElDZcAZeDI98K8xIQL0SXiS+bMW6+XUV6Y0vUtn0R9PJ9d44/xhfxhXJcN/5SDcVx4AOcTlKuncRD0yXIo5bbRfAIL+DdAHfJ3RivM5Fmo8R1778JeOzkWYGronhEqMv6U5Hutk41YwiTv2nQP83RD/bcjTOxThq6SSLoyEyEtTKlcp0hU6M256GKNUB5/KyDTFwgYDzNqiL/JjZGVTJvU2R5gCIGNxAgK4e6ikzP0uQPgAC53I8Bul+x3Xt704MXU/ItxD5sST5SX1lJPsuJFBv3Cu7lA3AtZegC/iPoZOlVrfi+Dz0gR8CiG/HD4vB4PoUrgV+iOHaLtxzB67dh2uBe3Eu5T7g8Xjuw7u3tXs9uOchpM+BvzrAxul0en/77bfnvV7vXT169FiCexSWcfnwetAnkOYJrMMO6EQPo/oMDm/hYbLf5VwCHl7LRVv22UkNl0LtpFaIeycHbsR/yO8qHLhVqgaER8sSyFSuljblX7EUP7x34ev3cIVBTvmPcBr4av4qtC/aUMk+gPI6iBiSTaESpLIOI6JP9O3DSKkv9qW+s5LuZHwpD6+k64F7R1TSHYt0IyvpjsKuWw9U0n2Op5JHVV4HXFJSMrryRh8wWHmVDQwMVEgDg3p/r5UDw5GDeMQGBm3J0917HgzgIWjLU5pON4K8X9MFR5B9cW/F6BMjyA6oXwvce4eWLjhFfBjSVdwb9AGfA13FiFTSI+1VuHesdm9Qdw3a9mIl3Q3gWmEog+luge6LSunuGjx4sPigKwLKKIaf7x89/6uuusq+adOmgkmTJm3REiKdFuWRBEggxgSWKM/SzspVWKT8pfi1LgOFJoXK/WOMi02J7AOjqypa0hL68yDrIYshfwdlDI4MJGAJAlh7u+aiiy6qMO6WaDQbSQImInAINljboDzHtG7Z4suOXQ+eiT3n2zTiniwR9VC4EfynyGFOiFxkepOBBEiABEiABOJCoA2WcuaNHDExOIO4Ji6FpkAh4Qy8+F5l+vlAiPgkZbQvftJfIH0gDCSQ8gSw9rbp5s2b5cG+jSnfWDaQBExMgOvgjXdOuCn6ociuLkR8nPKLSXzI8sDSKAgDCViCAHzyroKCgnA/hC3BgY0kgUQTkHXw+CwGHsZNdF2SpfxwBr4jGiFPBk+CyBP170H6QioekkKcgQRSmgB98CndvWxcEhGQveghy5OoygmvariRyVrUri1kGkSWXuG5hsAaeNExkAAJkAAJkEDUCcA33L5o5COD04qK29yo0mdkKPc/US/EIhmGM/Avg8HPEFnr+zFEHroTQy/rkxlIwBIE6IO3RDezkSYhIJvapKn0ZVmbNgdqhPXvPxVhN0f4itfSB2+8k8IZeNlEoAukDCKGvj9kB+QdCAMJWIIAffCW6GY20iQE6ilnJ2xisxo7guHBedlVzOZ2qrROeF3SWvHB4yl6+uAN9FU4Ay/ZbAjmJdtvyoYnpcFzHkjAEgTEB4+NhrbMmDHDEu1lI0kgkQQKlHdxlkoXuwQ7H3g1cYtCVbpQ6iQ+eBj4elOmTJFThggIhHvITq7dBxG430DOgHwIaQJhIAESIAESIIGoEpANbNzKfURhwwZ/bG7b+qdS5e6ANaryTgeGGhAIN4K/BfmdDrkUMhUyHXIhRPSPQhhIIOUJ0Aef8l3MBpqMQD3sOZH3+EOjUK39sGV1xVPzsfLBY2vtVzAzILPU8oIpeZnWkdiO+nMdlg+xTfYLuvOkiYYz8CejFU9D1gVb48VxDESm6mngg1B4SG0C9MGndv+ydclDIFY+eLx0agBeHlUxm52WlubEudi7QMDLpZLWNR3OwK9G68TIfxdoZfl/F+Ege9MzkIAlCNAHb4luZiOTgECsfPB46ZS80lkfZBfXlAjhDPxotHA25CxIC4g8Sd8OciaEgQRIgARIgARqRcCjnP28OXc/4iouadRXOdNcyvt6rTLkzXsRCGfgZe/tgyFXQWRzG3nlqIgsm2MgAUsQoA/eEt3MRiaAgFu5utmU7SUY90DpNmV/skSl/4yNbRaHqk6sfPChykoVXSgD3xiNq/BHIP6JrrGym51MZ+zU6RglgZQlQB98ynYtG5ZgAnbla2hTjrVYD9cqWBUHdFlVVStWPviqyksFvd6Qa+35GxEZvVclL2oJeSSBVCcgPni+Dz7Ve5ntSwSBBar0V5/y78Zz626f3Q6/t38Npuh/r6ou4oOHVDxVX1U66vcQCDWCfw2XL4GIz/1tyDcQD4SBBEiABEiABKJC4GilvLnKc/DFp549wVFW5nbPnHYnMsaAniFaBEIZ+DuQ+V0Q2djm/yCyNO5biBj7HyA+CAMJWIIAffCW6GY2MkEEcmFPml15yVy73V6YPXOaN1w16IMPRyf0tVBT9JJSHqT7GnITRB60k0X/ssGN7E8ve9LHMsiPjv1iWQDzJoFICdAHHykppiOB2BIQHzzfB2+McVUGXp+LGNvWEFkqJw9AOCHRDi5kOAoia+/FHbANUghZBOkLYSCBhBCgDz4h2FloChLAk9n793zl9ZPPeW7ChXhjmcNoE+mDN0pMqVBT9JJLU8hlkCsgh0A+gsjudd9BYrFMbhzybQ7pDVkGEeMuPyZk9kBcBPIGoYkQBhIgARIggSQjsFip9LrKtbbD7N9lgFh6iXK1naE8vU/jC8xi2pOhDLy8+/0EyCeQJyHTIGF9I7he23A2MugB0d5eJ/nhB1/gQb/bcXwQQgMPCAzxJUAffHx5s7TUJNBGpZ2Ml8Pttvn9sgzbgSfpOp+gXJ0wYSurtiIK9MFHhGmvRKGm6MW4y7T8dZBPIVi+EHhNrOzHKxKLd/XJVDx+zIUM50O7OeQVKkkgxgTog48xYGZvCQJ2ZcN3uL/C3mCDm3Ye5RFXbMSBPviIUVUkDDWCPxRXKzqiIuWeiBj8aIeRyHAyZChkKWQXpAGkK0TqeB6EgQTiTkB88HwffNyxs8AUI4D17Quwc91g5XC85MlwrU4vLOxTX6lNRpopPni+D94IsdA++PXGsohK6nnI5QiITNO3g4g/XkbtMi0/ExLp2shbkLYPJFToCOXyUBeoIwESIAESiC2BdOV5K2/82GYoZTFeAzsntqUxdyEQagSfKDIlKHiGrvAmiG+HRGrc5dYXgiLxymE0FPLHxUACEROgDz5iVExIAjElQB+8cbxmMfCvo+qjIPLARRfIs5AzILsh4vOXqftYP+iHIhhIYG8C9MHvzYNnJBAJAXmRzOYnx1xcf+u20y+HixXLsuS7vFZBfPCYopcVVQwREgjna48wi6gk64ZcMoM53YOjGPqWEHngrx1EdAwkEHcCXAcfd+QsMMkJYI1zCzxU90ez5SsOq7Nr1wkNlWvWn0q5atssroM3TtAsBl5f8144yYXIE5b/Qu6D9IQwkAAJkAAJmJxAmnIdD8+quFeVLbChjS0LD0DJZmkMcSZglil6abaM1tdBfoE0ghRAJMhT/fIQHgMJxJ0AffBxR84Ck5+ADMy0HU/9MPLtViu1trbNog/eOEGzGPi3UPULIPdDGkDkgburIbmQQRDxxzOQQNwJ0Acfd+QsMMkJ4Gn5P70q7dzi+g0+8DnSFqbt2HjtgUq5a9usaPjg8/LyPoQfv6HUxe/3i/3rmJ+f/52cS4DuNTzh/2r5WfL/bxYD/wxQikhoBZFtaiV8CXkaUusHNCQzBhIwSoDr4I0SY3oSkOF76Y8Tn3xkAgzmjIEDB26IBpNorIOH8b44GnVJljzMYuD1vGQqR5vOkel6BhIgARIgAZMSwBPz1xSNyL2m7o5dN1wLlyqelk7EXiompZPYapnRwCeWCEsnAR0B+uB1MBglgUoEPMp5HLadfbPetsAzdXhU3vUV9pfvXilZVE7pgzeOkQbeODPeYSEC9MFbqLPZVMME/MrW0ab8cKHa6snNMPbygHRMQjR88DGpmIkzNeMyORPjYtWsRoDr4K3W42yvEQI+5fkZ6esG73H7lH+LkfuNpOU6eCO0ytNyBG+cGe8gARIgAUsSmIPn5zYtWNS40ZIlbQFgSR2836NYedpvPOjQTzIKCqcXrF12tyXBmLTRNPAm7RhWyxwE6IM3Rz+wFoknkIu3jB6m0r/yTHrzGFdR0cUlynFBhir7FEZ+Vd6QQd9i+dlb2dnZtV4OV1VL6YOvikzVek7RV82GV0hA0QfPPwISKCcwQjmvwUrxo2HcA/52h3I8GU824oMvKCjgXvQGoNPAG4DFpNYjQB+89fqcLQ5NAA/U+XBFbzPah0r0JW4AADb3SURBVE4ZGy198Ma56jvL+N28gwRIgARIICUJYAncYSe/8fYhN9z30C3SwE3K8wGM/DZvuqvYb7Nv9St/QJ+SjU+RRtEHnyIdyWbEhgB98LHhylzNTaBYqQNsyv5551m/tERNu3iVK8upPMPeUe72WTfc9EHzv/8Zf/jM6V/HsxX0wRunzRG8cWa8w0IE6IO3UGezqRUE7MqFd4H4WwQVTr9SgS1er1SqbOVRh2+addVlyyoSxylCH7xx0DTwxpnxDgsRoA/eQp1t4abKdPyx73zQ4ZYRD8CGB8IS/F8UjMtrX5tr8UQd6YM3Tp5T9MaZ8Q4SIAESSBkCJSq9Mwz4/G7TvsNA3f8spuNbYjr+MRyP9tSpM9ju9c7ylhb+X8o02EINoYG3UGezqcYJ0AdvnBnvSC4C2Gr2ZtlkFgH/2fbHw3NYDqceg5G/O2/02HYlJSW3DxkyZGuiW0UfvPEe4BS9cWa8w0IE6IO3UGdboKnvKOXwKNfbV99137EYoRfvUqoRDPzfGLkHp+P9fruyNTUjCvrgjfcKR/DGmfEOCxEQHzxGMFtmzJhhoVazqalK4GLlfBrD9Evr7NzlQhv9dZTrhUeV54oRynUGpuMvc5aUfF/sLzHldLz44LFbXr0pU6ZE1D15eXnjkVCzcfURPwK6fO1m5PU+dt6L60oArex4HbXGx6s8lkMCJEACJBAfAjaM0u/akTvqiJuU690fledqTNm6sJZdjDuCzQan+5G5Svlyleea/DHj9issLLwsJycHq+RSIowpLS0N+B7SELxebwO0qsLVYLfbN6dEK8M0ggY+DBxeIgH64Pk3kKwE3Mr1IOo+vOH6DWLQLzxBuR7F295egZG/2GezNbf5fTDk/lHJ0j6jPvj+/fsvTpa2xaqe9MHHiizzTQkC9MGnRDemfCP+xMgcvvXXrh5233EYtf8Oy5aOL/dDMErXRusuDGXPcinvXK9y95hz0fmLy5TvEpy/mCxw6IM33lM08MaZ8Q4LEeA6eAt1dhI1FevWj+w6fWZTDMHlta2qs3K9AwN+dZ1du+RlLN0OUE6M1tVUjNA95c3yl+Bhuu8lLm9/++PcszZkqNJvyq8lx/9cB2+8n2jgjTPjHSRAAiQQNwKrYZPrb9oiI3HYcKVKVNqZNmX74ZgPPuycptJXwtgfBbUDl51yvfxo65GuPG9iydttGzp32oLjMKfy5pRf5/9WIUADb5WeZjtrREB88NOnT29Yo5t5EwnUkkChUi2aYcr9gieePbIUxnydUnXtyj4aRrxumrcURl2CbShG66+Wx+V/vxsPzz0nMUzBv/D5HYP/xPF5uSC6ZA3ig58zZ462fW6yNiOu9aaBjytuFpZsBOiDT7YeS976blKq3oDbh7157Z33nlKqnGPRElu6Sv8Jo/WDMvAudIzCmzVRrmH40p4HWw2bLsEvj4lnYrT+QZkqO+t/p560Ar71i3COJe+pFeiDN96fNPDGmfEOCxGgD95CnR3DpnaYs6B+g/Xr62pF7FRq/xsG5bx5bc49vfFQ3OOib6jS/1B+/6Xpu3fXwVK2fph6vx5GHYN2LdiwxE11LVIemWr3F9evX4Lz2RuUp4+kgE/925/7XLkSx6+0O1LpSB+88d7kMjnjzHgHCZAACVRFwNZr3MTTt7VufYhMp7fEC1tgqI/2T3p9apkzrbFHpX/zoXKfk6lcS/2lpQ0c5eu0b8WStrl4CA7PzNmCgy5bXZwfUaZsj2Me/uNSl7M0zePxlSnPPVlKbZmhPBnr7s6Z6bx3xMlX4g1vVVWGemsToIG3dv+z9dUQ4Dr4agBZ5LJs8Xroq2+c5K6X2X4Gdkc7TalSeUlL6dDhE9I83gNvUs418HPnY6naG+qvvy9q9dc/GTaVXlig3E3xXvXZNp9P2d3yQLv/uIuU6yqMvGWTleCzHbZM6A/COYrxj4CRDzwshzSvZyj37zD+h/16xSVvH/fWG+fhCfiVglzKz2/cyJNtIeNudB28cLJ6oIG3+l8A2x+WAH3wYfEk3cXWf/zZNL24pECrOLY1y9r0yus900vcvjlKvXu0Ut4ilXZi2Z33PuoqLmrVV7nWw5/90SUqfZp/9lxcVk4Y7tNhuLthZP2Po6h80zf4yR/3qrSFuH4eHmWrB0ONqL8wXTnPwfEfGO0uwTLxbnV/lk/ZPsRQfYjkB1nvV57JiCwtsWfuXn7MEQM7/frLtS5V+rvcg/IX5p9y0uaeb70RMO6is2IQHzy2l5VlgAwREqCBjxAUk1mTgPjguRe9ufte1oIvm/TmsfuvXe/DiBYPoOExcuW6uGhE7s11dxUMvkmpo2EVlmGq/GXvS69d6nK762OpWf1FqnRclnKtyJozrx7Msb+1cnUoUZ7rHcrxo3P37mCjbS8hrdsmm8b4/BhplweXcvTCPcuhby8axG0YozfH+UbIfsFk6dBttStfHn4AjC51Ot0Or2fFeuWdhJvcBfUa7VrV/ZA+B/708zWo31K554Uxj41zuVxndv31x5+CefAQJCA+eCN70RPcno34yYIESIAETEVAdmdb8s+SBq3nzGuGim2UysFI31Z09wOX1N2x/fLrlerihaGUteCdf5ktT5XLLm7tMUJ+GAZ1ar3tO+QWLB53feNVvgGIXQ3jjlluWTTuGHq48q/Aw2wePNiGUbkYaVvrNLwDHdu5rsL9bSUdgg++cDzBjqIrgr8Jpt2X4J4l0LfGUdagN9ip3N80QJVxvrCkXuYOPPk+AVPsn+O2z5cf0n3DmoO73dz93clXtpel7AiTnxmV5/f7Dzvkp5nyo4SBBKJOgCP4qCNlhqlEgD74+PQmDPeR/7z1TqcOP/96PR4Rz5+BwUdnlf51m5dePbpOwe4FMm2OKe1MGNb7MrdvbyS1SleuD11KjYNpxnJx8WMrOwzukTDU7WGUt0G3f3ntbRhJ+xvhNagyNR8w8LjeAOnkPLiWHKkxE7BbeebUVemr/NirXfLDfu0ZS1TZFx2V+o9DpX3qqVtnq7Oo8BH423/B9V5r23ceu6tJk4Pb/jbrWrxjFcN+zx94Y9nhuNYXe6Hfi2MgfDGo/28Oh+Osk9+djHox1IRAOB98fn4+fsBVhFb44XSoXofz79Eff1WksEiEBt4iHc1m1owAffCRc8NU+QGzfp2zf5FSrbAebK3cianyK9eNnXgQjnfDl/y4PKx2sXK9VYL3keMNZ+5i5WkFQ40RsW3uQTN/xB3+55FWzmEs/cfAuCMrmWq0iyGfCMH0N0wxAtJ0wNrvjQ5lL4VhDwTo2mOv9V9dyiUG3w+9rBP3fKTK3rlEpQ3yORx4bajNbSvzvAsf9zclytHPZrf/110nY4OzsOBGPPW2dI5yn974kMNfKUnPcDWd+8sthwRG72Wf4+2j52OK+BC8YjSwiYzk/+ndd/wXxqNX/99mrS+vAf+PFYFwPnifz6d/S1wR+mmnXoc+CsyaxKpuZs2XBt6sPcN6mYIAffABI33wDzDcmPDeDwZwu0ydd1HpE3YPv1+M9EdTledSPBneGSPs33q8/Y7LqdLXeJRPRrGHw7i+2PrP/8mDZA/iITQYYptMaV+iex95HuzkCs1o45hmV/4+fuUbL3HtjwD3dC5T9pkYbkteEuQLe1EdVTodPvKH/c6MR3x2x192987LYdnXYyR+wNbOh3zq8Hjm+lcsHnpl4Glz90k/XHb1eFdRyYrjPp36lGSCKfSPJ46fOBivDi2E4f5edHiSzpt3a/9PEd2v/9xfsGSdwQwEwvngBwwYgN+ODJUJVHyAKl/gOQmQQGoTuPjBx05afOLxreVJ8kZK7VqN6etmQ+4aX9SgwYn9lGukU3keKsaKMBjuqSdMfqcODPe2YuXukKacL8DPfWrmjp1ibHtdgneOwxj3Rryeq7h8oISR9Eic4/ulYn90bNJivxzGew6MPGbWJQTeR36UDIQxZY6Bvw2jdRl02/aHgX6zvnKN8mak+5wlniJMsWfDGP+LWYL2aw87+pP66ze8//2mNQ9LLtjY5Zm8cU+3xKjtLRjp5aLDY+wbJw699TOM3GYMHDgQt5WHP08/VR5mW6w+naqpeCSBlCVAA5+yXcuGRYOAmXzwbf74o1GZKyPoVy5v3cmvTz5mV6PGXWbAmJ6G6egNsm3pvQ8Ndmekn44lXq/IEius1+6iBg/7xG+3t4Gujkt5rsFo+k61bv19R0/9uK5Dpe8sUu62TuX6Qvl8XTK375DvhbsxVb7EoWyPwuI2cJaI4fb7Hco5BIY6HSPq4Egau6kq/0lI8zeMdA8YZ/weCBjpZhiFv4d0Z0OHh8T9HsQ340m4V3EcBB+3T3sfOfzZr2EDmJM8dTOvcRYXTS/0l/RBI3f+qTxNVl130xcdZv2W2+Wv33+QFsOBviJ/4H9+KS0tfXPQoEHc4EWgWCSE88FbBIHhZtLAV4MMT8Q0qK+c73qG3n08vhxnLVSentidytlUuSYX3zHieExRLlihPMfiEVt/F+V6vfiOe4+D7l9sH3nYEkz1nahcL5bgHc03Ydpyu3IfNAE7W41QznFFgenN9I1YT9tZvszwZfp48fD7T8ncsWPNTUp1kqlQ6O4runvkufV27DwXug5ZSm3Fw0i3Q3cp0l1xPaYt4VDcBN11eLL42rq7dt10nVKHYhi0BveWLxPaWXA77j0K37DLMBo7peTe3IEZO3c3uFGln4AR0WLce1TRvQ8OTS8sbHKjci3SDELxPbl3uUqKW2MDD/gzvfMwBGpbcs8D96Z53J37KucP8pARnKTNvMPvH2kv8x3eT6V95VSlP8o0rn34fbk+R9oJN6i0TzCFOm0TBlQZw+/P9WRknHODcpyXoco+X4xnpFoOGZ5buF/DU8H1EpQ7FeuQnYcOufuBba2aHwNdH+gmY97NgRHisE2PP3so6noTyn0FXWYrUc5Bm59+rht0/aHLk25E/IZ1z43viuNg6MaKDhwuX/P8C11gQIa6lHu06GDweq8d/wKewHaNwCj1Maj8MHgnLXtpUte28xYMy1FKRoZ4z6bzqNEzZh44YP3GgR+Xr1mW5VfdV7zw6rFNly4bslmpwbl4yhq6g1ZPePHU/ddtaAoH8Y1XYjpYjOrG0eN719+y5fgLMHXdRqlipOu649Gn+qTv2OHqo9TP6M8tKOOwgvseGlynsLAx+P+ONv8t/VSWc89jrpKSluCwGbr3ke7msvxJj9n9vvqI74/2ZeP4sv/nXy+H4U6HkV6zWrnbN1bpf/u3bm2OEax8tmejzCNgcf9UpaU4DYTzoUMV1T2QLEep2Eh/GYz71YjAaGvT4rY6NuU7HoYbM/K2drgmAYltqLbvLRzFmKMMvxdG+xWPcv+QodL7yfapdQsK1mGkfwn+NqV9XXc3btyn/pbNL/2ovMNOw4+QIvwtzb/4im+OnDr1VtleVTJG39ycP3psy8LCwstzcnICI+5D0KV5Rx2++Z9DDvpXDfldkjFYmEA4H7yFsYRtOg18WDz4BlTpczEd2d5VVITvSXXkYcqF7391Gb74jsQyGAfiB7VTrvtxPAq6MzN2FwjTds2U87FmytYQo5U+eEczvjj9zRsq53P3KNtm6G7G9CamKf3p9ZQLu1/ZfsXoJyc45VkX21hOciv1XxQ4FMYdX6gycnG+XaL8T+Mp4nsxwtpfdBnwf2L5zx142Pd1GHxR4Rva9QXW/VyLKdK9lgl54Ce1Kcf39bZuD6RDHWYUYHoV+c3J3Fauwxf2tyj3FJT7v3rb9+gwdjsBBuRvbdkR0n1VoFx4HaXtz/QdO9FseerJ/iUMx/G49xe1s0CeVEbU/gm+4E9GGR+rgt1N8cBUGurwvlfZzsQoMM9WXNzFVVwsI0G0Le18POU8wuYrPbHx6rUyhfsKjOQu8ccifknT5SvwG8U2EWXshu5YxAc1X7xUdM+hjBJM4e6PNo/CDmIYUdqegs4jT0mjEq+2/WOR8H8cZaCejr8dyv9x24WLcEk9ACOfhv79HHX9ocNsMSL++1BGBjYeeQVv7fo4Z9kq/J5TA5AffgR4n0AdP+8wd14rNLrrCOVqcAf2BYfufwcsXIRkqjt+jDQuUJ4b8Ifxd8t/8TMGBg1TzT9g//CLkO6v/VevER2WXqXP3qHcZ4DN/Kyt20SHYPsePxTPkX5KK4IZFI2y5cHg70C6F9MqjLT9ErdyfIVrl9t8/iyFDUxRb/nRea50BoL2uS7D3xWmwDElrWwHBq7ghxXa2wj8/wSMk4K6ojJsk4rROn7H+AcjbWAKHfe+X6q8q7AMrXdx/aySjIKdy7YozyAAke1Xi5cfe/SjB/w2V6bOwU8KcWcsuPWOH054bJT8CA40QH6I5D/6QBdMnQ8NlqXwA3R1/jlnbjhh6rsB467peSSBcATC+eDD3Wfla/IlxxCGAL4Mt+ALL8jJhi9+1R3nGLzaxLgjBL4Mj0TEi3jwi9WGdbW2Y3ATzit8kA7RwbhgYFPhg5R8j0EZjXXpbEh3FIxBC1zDgFAL9u7QtcUXMAb3WrC1x0Ya7aDDMiEt2BrDsLWHTrMauCDTqI7DENmopcLRX0c5jsBxrabDFz6mUZ3H4LhK0+Fet105j0MdV+p16TCyYLECOiQPBLRfHQQdeIlxrwiHQCfDxwAbxJ3YXxt1kZHgnmlePAmNHwe2A6APGBccMSr1wQAqSQtDLsHmwjl8vbZT9tbZLsa65guhQzsr0l2GDroSOvkBgWBzwWBfmab8ogvWL/DyjitwsU8gSeA/mxMX8WPIdTnaLH0gATr7+U7lRNn+pqJAPSTdCXha+2wdf+xSprpAB8Pp134h4QeErVGacpyJ2zCZEQh2/CCx11POE3G2LqiTPL1+5ToYhnWVpsPR51T2psh39R6dXxjJ35NWhlzKxJQ4/i796xHHoFqCTX5o/QF5G1LmsweeNl+zS3lf9yn3DdCp4qz6u1HuRxl4neijyjMcD6qNWdW92xo8nX42ZmS+RwbL8UMk66vB2QsXK88ROsP9+nf9bsAvrHLjLnnhF4R7a7sDirQ0omMgARJIHIHgF13iKmD2kvEl/yLquAlfsPIPX5z+J/HlrNfBsPlGwWi9hC9KMaCSzo3zJzC6Fn9j0Kj6i5HXaMhbSLOhvN3+InxJY5cr//vl5/K/vwhpJqOML/AFjdsDQXRfw5h/D13AYKEQcYrO9ynPLByDBhAz0nj7VKny/ApdJkScoaif3+3GWl4c8X2N/bjwZY/8GhRiqhwFiLEQgyC6ZoXK+wmuy3pi0Ym0KFHez3BE3hUvtWjiVl7c698ueUGPYGuIcuXVltg8pEJXx6e80PnnI4EYeRgxmcGw/Yi6QDSd2lSqfLPQ5mnQo74S/Ni92/ajtBtxT1AnbZG2faPTSb3+CN4rcQR5H7ZtDXTfIS6cEPxetHUbdOAlL/UI6EqhK0TaudAFRpw4gkPgB8U/SFH0HRBsA0bUownuFSMbLAMpMdWMXcpWQCecAgFta4/IEkjgB40oUUY7nyr7GXdo/eRHurZg+C108qMkwBr5tcLDZZ+g3Svgo3ZDpL3O+crzHsr5BueeMqcTRlytTFdl75Wq0lslf3fdOjtQv5cx3f11ofL0wo5pS3c0b7oaHXMBRtDz4YZ4YG2nDtnzzz93FmZyTsQvlN2oyLJX8sc2mfzkI1+mKc91yMafi3rkj3li5DcD//Mn8gLj8tBEqYJtbdsUy5S5puORBOJNQHzwfB+8Meo08NXwwhfky6WqrM+8889dgi/Ro3C+AD5RjIjKLl/Yu5foThHfM0YyH/vwHuYF55y5DN+T58i5+J+hO/ePs89Yinc0X4p7X0Xan2Aozlx0Zs/l+Fbv41Tup6D/HV/GXf455cTF7oyMbHwh34Uy/irFE8uLjz/2r50NG96DB6NuQJ6LoTtgxZHd/9jevOmoqcrdGxZ7pRdLgtYcctC8LW1aP/+v8vSAZV+PLTfbruvcae6mdm1fWa883TBtsBm6A7e0bTt3U4f272IauU0DGLxCPBewrXWrXzZ06vgp1iQ3x5TBjt3KfWhB06Y/bezYYQbWFLfGUHvrTuU5umD//X/e2LH9L2XK3Qn5bdquPKeU1K//08b27cTAdke56zYo97nuzDo/bWrf7l8wgp9fLVmhPFd6012zNrc7YCVY9kXbZDTYtywt7Xvo1mN6eCBYzViovIN8NttXm9u23QquNyLd+7Pgt0UXfbKtTSsxYvCjeydgWdZIGMMPd7RovgvXcsFr5EfKMwq693c2bSwG8JkPlefmUcr7HHRv7260P4y4P38Bpslx/4uI5+3efz/50fTqGjxTgXLkR9fzJVn1izCC/QAj1m7QTYXuqXXpLvcOh2MGDGc7GL2vUNeRnjp1Cr0ZLizP8rREf85CPrfh+YLdJXXr/ghfNNZ1exaivy9zZ9bdVpSV9QMYtgGHf9HfJxQ2yFq9s2mTANdgP3Xd3rzZ7+DwZYlyN2uEp9lnYep+Zfduk5cce/R7O9C3R+NHWpry9lt45mkj515w3pQflUem3fFroezTL3MG9f5yyK2voV2DoJO3l2x/bdzTV7yfe+8H+Hv5VHQSPs+5bcb83r2Wwje/oVzD/0kguQiID76goAAfJYZICdDAR0BKDPX8C85dhy9RGYkGAr7Yf5h7YW/R/aLpEP917iUXrsG173S6ebMvu2gNjMOXmg4G4M/frrh0FY4faTp8Gf8765qrlrwwKrdiNA/jvXzmjdf88WbuPf9FOtiqwFPEq6Zn3/zre/ff/faVwZEyfJprv7ptwIyP77tr8iHBUZYY4M+xTOjju4a+3QYzsXKv6D4acceUT+8aMhlO/J2iEyP/wb3DJn0+7PZ3xJCLToz8uw/d+/ynw25/T/IWnYzi3hn1wGOf3TUUhqN832wZCb799KMjPh0+9CO0RaaClZT11jOP3/bJ8KFfgANGreVTt5NGP3HTJ/fcMU3jIPV8bfyz//fx3TmzcG+gzWLI8p976vKPR9wxByzfkHtPwygfBvzyD+8bvgC68aKTduMHz1Uf5I6Yh2uPQyXz7qK75v2HR86F7l45z8UvLehuemdUruR3m+Qv9yOe885jD87G8RYMtwMjfNwzfPJTj34//ulHb5B2STroHix+7pkPv3jmsT5iOEWHqezRb4554u1Xn3k8Gzw3iw75vPbGmCdemDz68dszg1PuMgJ+4+lR4956/MH7wXCNpJN+n/LEw2Pee+i+MRpXyeP9B+55AWzeQnyTpJM2Txtw81cz+147U7iLTsKcyy76Y1GvM/6V6+UaFNaly64tbVtXpNH0PJJAqhEQHzxkeaq1K5btoYGPJV3mTQIkQAIkQAIJIlDhJ0xQ+SyWBExNwEzr4E0NipUjgRgTEB98WlraAdjrf5quqAbY4Gh/6E7QdHhi5lHsbDddO7fy0YwGXuqE2cryKVErdw7bnngC3Is+8X3AGpCAEAiug7dv2LDhrHBEcnNz8bgLgxAwi4GXJ7lzIddBWkFskCKI+FuegbwKYSCBuBOAz4/vg487dRZIAvsSEB88Ruv1sKcCDfi+eEJqzGLgx6F2zSG9IcsghRBZJ30wZAxEnpycCGEgARIgARIgARKIgIBZDPzZqGsPyAZdneUpb3kK+3bIgxAaeEBgiC8B+uDjy5ulkUBVBMQHj7f+tajqOvX7EjDLU/SLUDWs/gkZzoc2sBwp5FUqSSCGBOiDjyFcZk0CBghwHbwBWMGkZhnBj0R9JkOGQpZCZAMTLNFWXSFSx/MgDCQQdwL0wccdOQskgZAENB/8lClTQl6ncl8CZjHw81C1IyAyTd8OIv54GbXLtPxMSGCTFxyrC7cgQZ8qEnWEnpskVAGHahIgARIggdQiYBYDL1RlR7EZOrzyYJ08XR+pcZdbXwiKxCuH0VA0q6zkOQmEI0AffDg6vEYC8SNAH7xx1mYy8JVrfxkU4pe/ufIFnpNAvAjQBx8v0iyHBPYhYB8/fnwnTTt37txWHo+nqV6HjW/WYdmcLKlmCEHALAZ+MerWuFL9ZPQu9RND/yGkL4SBBOJKgD74uOJmYSRQQQBr3uvAgA/XFMcddxxek6HwGgdVoSsrK5Ml1gu1NDzuTcAsBl6M9yuQNyGvBat4MY7ik5fOlHXxDCRAAiRAAhYhgC1nC/v37/8fizQ3Js00yzK5H9E6vOxLdYI8CxGDvgUib/VaGYzjwEAC8SUgPvjp06fjZXIMJEACCSbQAeUfnuA6JFXxZhnBCzRZGnc9BG/6DDw5/yuOZRAGEkgYAfrgE4aeBZNAZQIyPS87nDJESMAsI3h9dd/BydkQ8cnrd7bTp2GcBOJCQHzwF110kcwmMZAACSSWwCIUL8umGSIkYKYRvL7Ka3BygV7BOAmQAAmQAAmQQOQEzGrgI28BU5JADAlwHXwM4TJrEjBGQHzwMkU/39ht1k1NA2/dvmfLIyBAH3wEkJiEBGpJAE/Mp+fl5Z2hy6Yb4vX0uscee6xo5cqVTl0aRqshYEYffDVV5mUSiB8B+uDjx5olWZpAOlovy6IDgjXwMlKXvVAqdCNGjFiLc/rgASHSwBF8pKSYjgRIgARIICYEYNB3YUe6vJhkbuFMaeAt3PlsevUE6IOvnhFTkECcCNAHbxA0p+gNAmNyaxGgD95a/c3WmpoA18Eb7B6O4A0CY3JrEeBe9Nbqb7bW1ARkHTyDAQIcwRuAxaQkQAIkQAIkkCwEOIJPlp5iPRNCgD74hGBnoSlMAA/UtcDytxd0TTwIy+S80PXUdHhL3MODBg1arZ0Hj/TBVwJS3SkNfHWEeN3SBOiDt3T3s/ExIABjLls/P6VlbbfbM71er3I4HBVvDYWB36Rd1x3pg9fBiCRKAx8JJaaxLAH64C3b9Wx47Ah48RrYxTXInj54g9DogzcIjMlJgARIgARIIBkIcASfDL3EOiaMAH3wCUPPgkmgMgH64CsTqeacI/hqAPGytQnQB2/t/mfrTUWAPniD3cERvEFgTG4tAvTBW6u/2droEsDDcraxY8fKPvOBgCfoHT6fL02vGzx4sFu7Xs2RPvhqAFW+TANfmQjPSYAESIAEokIAT8Z3xlPyd+syawoj73a5XNmaLj8/vy/2oV+vnfMYPQI08NFjyZxSkAB98CnYqWxSPAn8gyfmz4lSgfTBGwRJH7xBYExuLQL0wVurv9laUxOgD95g93AEbxAYk1uLAH3w1upvttbUBOiDN9g9HMEbBMbkJEACJEACJJAMBDiCT4ZeYh0TRoA++IShZ8FJRgBb0NqfffbZOrpqp+EBO5del5OTU6y7bjRKH7xBYjTwBoExubUI0Advrf5ma2tF4LDMzMyHtBxg8Fsifgp0uzUdnpi/Gk/M79TODR7pgzcIjAbeIDAmtxYB+uCt1d9sbc0JYPnbPBjvl2ueQ7V30gdfLaK9E9AHvzcPnpEACZAACZBAShDgCD4lupGNiBUB+uBjRZb5koBhAvTBG0RGA28QGJNbiwB98Nbqb7Y2MgLYoc6Wm5vr0qW2yxa0eh3iHt31aETpgzdIkQbeIDAmtxYB+uCt1d9sbcQETmrevPk4LTX8760RPwq6Ik0HA39hlI08ffAa3AiPNPARgmIyEiABEiCBcgJ4icwPgwYNepU8zE2ABt7c/cPaJZgAffAJ7gAWTwJ7CNAHv4dFRDEa+IgwMZFVCdAHb9WeZ7s1Ak6n04b1607tHNPxNvG3a7r169f7MRVfql2P4ZE+eINwaeANAmNyaxGgD95a/c3W7ksAu9Gdh01r/k+7gnhbGP0DcQy8xx1+9zJcO1e7HsMjffAG4dLAGwTG5CRAAiRgJQJut/uzIUOGvGKlNqdKW2ngU6Un2Y6YEKAPPiZYmSkJ1IQAffAGqdHAGwTG5NYiQB+8tfrb6q3FvvHXwLd+rY5Dx4yMjPehC/jYMS1f0L9//wt01+MZpQ/eIG0aeIPAmNxaBOiDt1Z/W721hYWFb+GNby+ZlAN98AY7hgbeIDAmJwESIIFUIDB+/PjD8QDdQbq2tKhXr97lEydO9IoOD8sXYrT+ie46o0lGgAY+yTqM1Y0vAfrg48ubpcWPAAx4BkproJWI6fcfIJk494sO1832MjL64LXOivBIAx8hKCazJgH64K3Z76nW6ueff74zRustdO0Sw54Og/636HBNRuv5uutmjNIHb7BXaOANAmNyaxGgD95a/Z2qrU1LS+sCY36Urn0rMEI/TTtHfCPic7Rzkx7pgzfYMTTwBoExOQmQAAmYmQB86L1gsDvr6tgS8XbQbQ3q1mdnZ+fqrjOaogRo4FO0Y9ms6BCgDz46HJlLXAlsR2lrtRKxrexrMO76c83Qa0mS5UgfvMGeMqOBlzrVh8gfKQMJJJQAffAJxc/CqyGQl5f3OIz38VoyTMN3gT/9Sd35bwMGDLhLO0/yI33wBjvQLAbehXrnQq6DtILYIPJe4eWQZyB8LSEgMMSfAH3w8WfOEkMTwGYzz8KAd9NdPRRxD3SeoG4mHpTrqbuealH64A32qFkM/DjUuzmkN2QZpBCSBTkYMgYiyzkmQhhIgARIIOUJYGT+AhrZUdfQ7jDkZRity+BHwpeLFi26oFu3br7yU6W+/fbbirim49HaBMxi4M9GN/SAbNB1x07Ef4bcDnkQQgMPCAzxJUAffHx5p3ppMNzyPRd49SoMtixVawzdt7DbjaTt0LkRb4uoDGoCAT709zZs2HCWdi5HvJ5V1qoH1qvr9Skepw/eYAebxcDL1Iss2Xg7RP3Ph25zCD1VJBBzAvTBxxxx0hWAqfKK9eQwyGKY68FIy0BEC/vDSHdFuoVQOILKEhybQ3+KpsO98xHfAvkLcRwCm8t8hyfcZwRO+F9lAvTBVyZSzblZDPxI1HMyZChkKWQXRH7ddoVIHc+DMJBA3AnQBx935DUuECPdtNGjRzfUZZBeVlbWGFuynqTTtYCRdcEgi/tPCwciYodBlmeAAgEG14F0daC7V9PhWABx4tqdmg5p/sW5TJtXPOiG+I+oy8942G05joEpdaT5edOmTYu1++SIUTin1PVAqo/TB189o71SmMXAz0OtjoDI9FU7iPjjZdQu0/IzIZFORf1/e+cebFdZ3uEkJ7cTkEAgUANKMCCXaGWAoq2FRqC1VEXRgvBHtVrbUmQyOCMXO3VwWsfOtKAOaNTWoaKtl8kAFsdRESUtWsHKHZEiAjEhgQQSQhIgJ7c+v5X9nWxPzsnZh1zOXus878zvrG996117fe+z9tnvd9mX8/B9GxrMTqBy2WAHrJOABLqXQE9Pz5F8tvuMthbOIXleRvJ9Y6uO/Ll1KnVnTps2bWbxo+7xSZMmzWO/v46EfD/7h6MZqFi+4OUF/JeUCjoGWR5ch38GG5XxQyy/uuSSS/L+IE0CtSDQLQk+sDKF1T41lamt/u9FjkMH9m180iEYzN5J5ZTBDlgngaEIuAY/FJmR1V999dVTXnjhhXxapjKSaQ9J+zQS6NxUsB97BT9XSt7+wuu3eY3LT5TuP3ny5KPZ9rbqXsTvu5SXojtSxyh5Cx8FuzZlrdEEXIMf4e3tlgSfN51k2itTZZ9Br25t08v+JjofbUDDWabQosEsMwIHDHbAOgkMRcA1+O1kFixYcAaj6YO314w7mKnur5OkZ7fq8tHW40jQmUotfuso7ztlypT7Ufn/W0uS3sSIO0tz+6LY09TdyGM9xPY7qSBvr7/wwgtvSlmTAARcgx/h06BbEvw/0+6st9+FvoHSc38XSi/9U+gdKPV7zXjh+iIvNke2XfA46pZSl1mFjDhWsXkZL2aL2eYjfbFnUd5w8xh+1Vogfnkxm4bfIxw7ME5Ypvl68XsYv2r6EJ/MYExkivFufMuLY/X51t7e3lvxrerwD5s+vlv6ZPwOoVyNfqhfx2PMK3Wt+jW8iP4JdQdlP4bPM2w2UPdPVcW2P6uo30zdpW116RD1cN33ljoeawUvuvvi9+ZSx3kruHZe6NMRK7aCwlH4fZlttQbJlOcKfI/C79PUpUOXtixncyh+H2Vbza5Qt4zHO4i6v+Fa5Z3Ey6nfjxHf2Ryr6ni8xDGNH9F4Pe2qRob4pHM36ZprrplFXfXmJrYbqB/Pemf/6BGfjtc+67wGz6h5JlPUFX9Y5rk3FYZ/BsPCK/fhMO7JDdRVz2FYraE8l7qH2upW4zcdlvlfrO4d2wfwvQXlOXw7+0nIi7kv+R9OUq+Mae2+yy67LPdFk8CuEkjHURsBgeqffwT+e8r1YR74JJT1rvTqk8wuQrHfRh9HZ2VnF+zdnJsRxOd34TH21qm/cV/OOeecCXPnzi0vrOOYxuzhxXQCI6L0aMdt3Lhxa17II15gqw5I6jm+MX68CJeOxTiO9+H3G3W4pnOQulk5L8ZILR2TCbx4H7atpr9TM4H92aWOx1+Jb5Jpps8q47ynOC9J5JUo/vnpyWXU97KdxbYkmCTzl3E4MzVVLGzTqUvnKCO7HIstxy916QSUUeBKHifH08aqA8P+asq91CWBl05S4sj18vGjqjNF+XmUeNeXOsrpYMWS4KqOE+V0sPL+jyS46vHw28TxzCatQuXxqN66lvrUlXPTgVnDfp7TpS2pe45EmfXeqs0ciz3LuVuo679P1OWak6jv9+P4KvbTwWm/Rol5OvXFnqQQVmFaPZc491HOzRvE8lnqqvND+U7K+aKUp1BVx/28n9u5nOdJOniV0Zl8lnd2P1323UpAAiMicBXe/4HuGtFZu8F54m54jN3xEI/yIMegn6Ivov6kQvm16BE0lixJpd8WLly4Oeqv2F7odGT0+PZTLI2QwJvwv58ZgHXlvHSwSHqTpk6dmk5HOk1bkzzTcerr6+tP0iTyPpQE25+kN23atJZzk+j7/Ti+mqS6leTan6TxW8na8xa2VWco18Eyg7I5HYRtu9W1V8+fP7+T5atyilsJ1JVABhH7oXvqGsBYbfcfEXima98+AMAn2M9o5DUD6l/K7rs56YKXcqLnjGkC7yL6/hHzmCZh8BIYXQLJA6eObhNe0tUzgj/hJZ25iyd1ywj+ZuI4GvVPL7fi+hbbTM9nSlWTwGgQuH40Luo1JSCBHQg8sEONFTsl0C0JPo3MWmXUbj9p37EsAQlIQAISkEBnBKo3QHXmqpcExiSBrMHPGJORG7QEuotA1uCP764mdXdrTPDdfX9s3egTSHLv/wTD6DfHFkhgzBLIp0LyJjutQwLdNEXfYZN1k8BeJeAa/F7F7cUkMCQB1+CHRDP4AUfwg3OxVgISkIAEJFBrAib4Wt8+G78XCLgGvxcgewkJdEDANfgOILW7mODbaViWwI4EXIPfkYk1EhgNAq7Bj5C6a/AjBKb7mCPgGvyYu+UG3KUEXIMf4Y1xBD9CYLpLQAISkIAE6kDABF+Hu2QbR5OAa/CjSd9rS2A7Adfgt7PoqJQfwhgrli9I+Da6u4sCnkdbyq+YdVGzdrkpU3mEjWiwH8jZ5Qffyw+QX1krcWRJK2riPcvXRK9HTbP8umB+jCe/MNgky/MwA7T84mHTLD+w9N+DBJVfSMz/Y92+ujwdkz9ETyBtDBFY1NBYrySuExsY2ynE9PcNjCshLWpoXNcS1xENjC0/zHVxA+NKSLc2NK69HlZ6gJoEJCABCUhAAg0jYIJv2A01HAlIQAISkEAImOB9HkhAAhKQgAQaSMAE38CbakgSkIAEJCABE7zPAQlIQAISkEADCZjgG3hTDUkCEpCABCQggdEl8PLRvfweu3q+vz2fZW2a5fP9BzQtqFY8TX0uziS+Jn4ld5O/l72pz8WGvnQYlgQkIAEJSEACEpCABCQgAQlIQAISkIAEJCABCUhAAhKQgAQkIAEJSEACEpCABCQgAQlIQAISkIAEJCABCUhAAhKQgAQkIAEJSEACEpCABCQgAQlIQAISkIAEJNBOYFL7juWuJTCelvV0betsmAQ6JHAFfr9u000dnlcXt/1o6GJ0Rl0aPEw786LzKXQ3ehB9CDXFzieQH6J70b+jY1GTLPH9rCEBfYQ47kOPoZSbZPn69IXo8iYFZSxjk8APCPstKF87GeWrUJtk1xLMatSUBD+fWK5HeRHaBz2B3oDqbr9FAE+iQ1qBvI/t91rlum/y1cKfQSvQnXUPhvafg36EpqPct3vQmagJdiJB3IZWIRP8brij/tjMboC4Cw/xOs69HR2FJqIXUVPsHQSSeB5uSkDE8QX052hLS/m+/SZMJeZ14Fz0FIplFP97Van+f04nhOfRe+sfShXBH/M3MyxrUDplX0NnoyZY7tHVKDFpEqg1gVfQ+j70AFqK8g97GmqCHUwQGS1liv4OdAZqkp1HMJnu/RJqYif588T1ddQkm0cwTRjBf5843t52Y5IU/7NtvwnFzxLE5U0IZLRjaOKL02gz7fT6vTheh34fHY6uQk1ZT8tI9wr0HGqibSWorMGfhI5tWIAfIJ63oQ83LK6mhHMggaxvCyazE1ku0iSwAwET/A5I9ljFv/LIGbFHKT+M/hI9izajBehUlJ+3rJO9mcaWuLLentHtnFYAb2W7P3oDmo3qZlkLLLFlarTYNyi8B/0YXVQqa7Qd+FwsTf9rCh9HmXFZWiprtB34XKxR0ztu6tN4ZmasWMrLyo5bCbQTmNi+Y3mPEvgHHv1zrSs8w/b4lr7UqpvCNslkbWu/Lpuf0NAk8Fg6KiejdehvUWwWOh89hB5HdbI30diyxv4I5fejn6MsO8RSPqsq1evPwOdiWp+p3o+hJPdfoDrawOdiHWMYrs3peGXGr9hsCkvKjlsJSKA7CBxKMzKF/UqUJPKP6EbUNEsyTNJogl1AEN9DE1FmJrIO/3eo7nYEAaRT9gdoRpsoNsbmEUkT1uAzk3QvSsd5NvolylJRk+yzBHN5kwIarVjyQqWNDoEnuOzH0C1oCsr09p8irXsJfJmmnYLKCPcGyld2b3M7btmFeGYdd9GAM1KXNV6tewikg3kuyuzRiyjvd0lHU5OABLqQwHjalDfOaPUhkMRn57g+96uJLc3aewYGmgQkIAEJSEACEpCABCQgAQlIQAISkIAEJCABCUhAAhKQgAQkIAEJSEACEpCABCQgAQlIQAISkIAEJCABCUhAAhKQgAQkIAEJSEACEpCABCQgAQlIQAISkIAEJCABCUhAAhKQgAQkIAEJSEACEpCABCQgAQlIQAISkIAEJCABCUhAAhKQgAQkIAEJSEACEpCABCQgAQlIQAISkIAEJCABCUhAAhKQgAQkIAEJSEACEpCABCQgAQlIQAISkIAEJCABCUhAAhKQgARqTGAGbZ9cs/ZPob0H1KzNNlcCEpCABCTQEYFP4/XRjjyHdkqi/BaahD6MbkB7wk7mQR/s8IGvwe8jw/hO5XjaPXEYPw9LQAIDCEwYsO+uBCTQTAJJ6v+CNtYsvBdp71fRRTVrt82VwKgTMMGP+i2wARIYEYFD8b4SLUP3odNQsXdSuActRZeiW1BsJroAfSc7w9hxHL8VrUGL0YdQ7LXoOrQAPYO+i16FFqElqPhRrJYB/o3tavR9lDbHxqNPouXoNnQYKjbUdXP8m+gSND07mgQkIAEJSKApBNqn6P+LoJI8kzT/Cq1Fs9ActBKdjY5F/4seQ7Ez0U1VadufnU3R34VLkuk+KB2GTWgG+h20BaXjcDi6G61Ap6PjUZJ+lgFORltROiFpVzoFpWPxQco/Q8eg89AGVKboh7ouLpX9kL+ntMpuJCABCUhAAo0gUBJ8RrxJnmVEnOCSaJM4M4V9Myr2fgolwV9M+XPlANudJfiTON6DsuZ9AkoH4miUBL8eFUsCb+80/B/78UmC70P7olg6G2lz9n+A0s5i/0OhJPihrlt8v0LhA2XHrQQkMDwB37gyPCM9JNAtBA6nIUvQE20Nup1yRsq9KKPgYhnBF5tNIaPtTmwmTrehjLLvQUn2ZSkvywLFnqfwUNlhm6Qe34zyf47WodgvUDoGaeMcdCcqlrYX29l145P2H1Gc3UpAAsMTKP+4w3vqIQEJjDaBlTQgiXL/toa8hnJG6j9Fx7fVv66tvJhyzhvOMhV/PboKxf90NL4lNuM2508H1n6t2fjvg55Ev0bHoWKvahWGu27cXo4ShyYBCXRIwATfISjdJNAFBH5FG5LMM1WdxJuEfiLKSPhm9LvoNJSp/L9Axe6jcFTZaW0ns01iLUqnoUyr30I5714/H01F+WjdSOxgnN+I0sb3oR+h51Cm6M9FSfiZjTgVxTq5btp/b+XtHwlIoCMCTtF3hEknCXQFgYyg34O+iuajJN8PogdQ7GJ0LcpUed7YVkbSSfDHoCTcrSj2FpQ3xhXLFPgh6DqURJpjD6J0Hl6NHkedWs67EuXx8ia9vPEv9gm0EP0yO9gd2zbVyH6o66YteZ06EpU4W6e5kYAEJCABCTSPQEbJSdjFjqCQKfViGSkvKjtsb0Rnte3vrJgR9rSdOXR4LOvqg9l0KtMJGWhDXTczCV8Z6Oy+BCQgAQlIYCwQSEJegq5Al6JH0VtRsTkUMvVeR7uNRmfZQZOABEZAoGcEvrpKQALdS2AjTfsaOhDlvTWZDv8xKraaQqbLF6MNpbIG24NoY5YPslSgSUACEpCABCQgAQlIQAISkIAEJCABCUhAAhKQgAQkIAEJSEACEpCABCQgAQlIQAISkIAEJCABCUhAAhKQgAQkIAEJSEACEpCABCQgAQlIQAISkIAEJCABCUhAAhKQgAQkIAEJSEACEpCABCQgAQlIQAISkIAEJCABCUhAAhKQgAQkIAEJSEACEpCABCQgAQlIQAISkIAEJCABCUhAAhKQgAQkIIG9TeD/AWGnyN1SOx9FAAAAAElFTkSuQmCC" alt="plot of chunk unnamed-chunk-3"/> </p>
<pre><code class="r">coef(cv.lasso)
</code></pre>
<pre><code>## 14 x 1 sparse Matrix of class "dgCMatrix"
## 1
## (Intercept) 1.0894
## zn .
## indus .
## chas .
## nox .
## rm .
## age .
## dis .
## rad 0.2643
## tax .
## ptratio .
## black .
## lstat .
## medv .
</code></pre>
<pre><code class="r">sqrt(cv.lasso$cvm[cv.lasso$lambda == cv.lasso$lambda.1se])
</code></pre>
<pre><code>## [1] 7.405
</code></pre>
<h3>Ridge regression</h3>
<pre><code class="r">x = model.matrix(crim ~ . - 1, data = Boston)
y = Boston$crim
cv.ridge = cv.glmnet(x, y, type.measure = "mse", alpha = 0)
plot(cv.ridge)
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-4"/> </p>
<pre><code class="r">coef(cv.ridge)
</code></pre>
<pre><code>## 14 x 1 sparse Matrix of class "dgCMatrix"
## 1
## (Intercept) 1.017517
## zn -0.002806
## indus 0.034406
## chas -0.225251
## nox 2.249887
## rm -0.162546
## age 0.007343
## dis -0.114929
## rad 0.059814
## tax 0.002659
## ptratio 0.086423
## black -0.003342
## lstat 0.044495
## medv -0.029125
</code></pre>
<pre><code class="r">sqrt(cv.ridge$cvm[cv.ridge$lambda == cv.ridge$lambda.1se])
</code></pre>
<pre><code>## [1] 7.457
</code></pre>
<h3>PCR</h3>
<pre><code class="r">library(pls)
</code></pre>
<pre><code>## Attaching package: 'pls'
##
## The following object is masked from 'package:stats':
##
## loadings
</code></pre>
<pre><code class="r">pcr.fit = pcr(crim ~ ., data = Boston, scale = TRUE, validation = "CV")
summary(pcr.fit)
</code></pre>
<pre><code>## Data: X dimension: 506 13
## Y dimension: 506 1
## Fit method: svdpc
## Number of components considered: 13
##
## VALIDATION: RMSEP
## Cross-validated using 10 random segments.
## (Intercept) 1 comps 2 comps 3 comps 4 comps 5 comps 6 comps
## CV 8.61 7.170 7.163 6.733 6.728 6.740 6.765
## adjCV 8.61 7.169 7.162 6.730 6.723 6.737 6.760
## 7 comps 8 comps 9 comps 10 comps 11 comps 12 comps 13 comps
## CV 6.760 6.634 6.652 6.642 6.652 6.607 6.546
## adjCV 6.754 6.628 6.644 6.635 6.643 6.598 6.536
##
## TRAINING: % variance explained
## 1 comps 2 comps 3 comps 4 comps 5 comps 6 comps 7 comps
## X 47.70 60.36 69.67 76.45 82.99 88.00 91.14
## crim 30.69 30.87 39.27 39.61 39.61 39.86 40.14
## 8 comps 9 comps 10 comps 11 comps 12 comps 13 comps
## X 93.45 95.40 97.04 98.46 99.52 100.0
## crim 42.47 42.55 42.78 43.04 44.13 45.4
</code></pre>
<p>13 component pcr fit has lowest CV/adjCV RMSEP.</p>
<h2>b</h2>
<p>See above answers for cross-validate mean squared errors of selected models. </p>
<h2>c</h2>
<p>I would choose the 9 parameter best subset model because it had the best
cross-validated RMSE, next to PCR, but it was simpler model than the 13
component PCR model.</p>
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