Dear All, I have found differences between glmnet versions 1.7 and 1.7.1 which, in my opinion, are not cosmetic and do not appear in the ChangeLog. If I am not mistaken, glmnet appears to return different number of selected input variables, i.e. nonzeroCoef(fit$beta[[1]]) differes between versions. The code below is the same for 1.7.1 and 1.7, but you can see that outputs differ. I would automatically use the latest version, but by looking at the ChangeLog I wonder if this is a bug or expected behaviour, as this change is not documented.
Thanks in advance. DK >############# glmnet 1.7.1 > library(glmnet) Loading required package: Matrix Loading required package: lattice Loaded glmnet 1.7.1 > set.seed(1) > x=matrix(rnorm(40*500),40,500) > g4=sample(1:7,40,replace=TRUE) > fit=glmnet(x,g4,family="multinomial",alpha=0.1) > dgcBeta<- fit$beta[[1]] > which=nonzeroCoef(dgcBeta) > which [1] 1 12 15 17 19 20 34 39 42 58 60 62 63 65 71 72 73 77 [19] 80 82 85 86 95 97 98 99 106 110 113 114 119 120 123 124 128 130 [37] 136 138 139 143 148 149 151 160 161 162 173 174 175 176 177 183 186 187 [55] 188 190 193 194 195 198 199 204 206 218 224 238 239 240 241 245 247 250 [73] 252 255 256 258 265 266 270 277 278 281 287 293 294 296 297 300 306 308 [91] 311 316 317 321 326 329 336 337 341 349 354 356 363 365 368 374 376 377 [109] 379 384 385 389 397 398 400 403 404 407 415 417 418 423 424 430 432 437 [127] 440 442 446 450 451 454 456 459 463 467 470 472 474 478 481 488 496 497 [145] 498 500 > # just to check that inputs to glmnet are the same > g4 [1] 5 4 5 3 2 6 1 6 6 1 3 6 1 2 6 3 7 2 6 7 6 7 5 1 3 2 2 3 2 3 3 1 5 6 7 4 6 3 [39] 2 7 > x[,1] [1] -0.62645381 0.18364332 -0.83562861 1.59528080 0.32950777 -0.82046838 [7] 0.48742905 0.73832471 0.57578135 -0.30538839 1.51178117 0.38984324 [13] -0.62124058 -2.21469989 1.12493092 -0.04493361 -0.01619026 0.94383621 [19] 0.82122120 0.59390132 0.91897737 0.78213630 0.07456498 -1.98935170 [25] 0.61982575 -0.05612874 -0.15579551 -1.47075238 -0.47815006 0.41794156 [31] 1.35867955 -0.10278773 0.38767161 -0.05380504 -1.37705956 -0.41499456 [37] -0.39428995 -0.05931340 1.10002537 0.76317575 > >################ glmnet 1.7 > library(glmnet) Loading required package: Matrix Loading required package: lattice Loaded glmnet 1.7 > set.seed(1) > x=matrix(rnorm(40*500),40,500) > g4=sample(1:7,40,replace=TRUE) > fit=glmnet(x,g4,family="multinomial",alpha=0.1) > dgcBeta<- fit$beta[[1]] > which=nonzeroCoef(dgcBeta) > which [1] 1 2 3 4 6 7 8 9 10 11 12 13 14 15 16 17 18 19 [19] 20 21 22 23 24 25 26 27 28 30 31 32 33 34 35 36 37 38 [37] 39 41 42 43 44 45 46 47 48 50 51 52 53 54 55 56 57 58 [55] 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 [73] 77 78 79 80 81 82 83 84 85 86 87 88 89 91 93 94 95 97 [91] 98 99 100 101 102 104 105 106 107 109 110 111 112 113 114 115 116 119 [109] 120 121 122 123 124 126 127 128 130 131 132 133 134 135 136 137 138 139 [127] 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 156 157 159 [145] 160 161 162 163 164 165 167 168 170 171 172 173 174 175 176 177 178 179 [163] 180 181 182 183 184 185 186 187 188 189 190 191 193 194 195 196 197 198 [181] 199 200 203 204 205 206 207 208 209 211 212 213 215 216 217 218 219 220 [199] 221 222 223 224 225 226 227 228 229 231 232 233 234 235 236 237 238 239 [217] 240 241 242 243 244 245 246 247 248 249 250 251 252 253 255 256 257 258 [235] 259 261 262 263 264 265 266 268 269 270 271 272 273 274 275 276 277 278 [253] 279 280 281 282 283 285 286 287 288 289 290 291 292 293 294 295 296 297 [271] 298 299 300 301 302 304 305 306 307 308 309 310 311 312 313 314 315 316 [289] 317 318 319 321 323 324 325 326 327 328 329 330 331 332 333 334 336 337 [307] 338 339 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 [325] 357 358 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 [343] 377 378 379 380 381 382 384 385 386 388 389 390 393 394 395 396 397 398 [361] 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 417 [379] 418 420 421 422 423 424 425 426 427 428 429 430 432 433 434 436 437 438 [397] 439 440 441 442 443 444 445 446 448 450 451 452 453 454 455 456 457 458 [415] 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 [433] 477 478 479 480 481 482 483 484 486 488 489 490 491 493 494 495 496 497 [451] 498 499 500 > # just to check that inputs to glmnet are the same > g4 [1] 5 4 5 3 2 6 1 6 6 1 3 6 1 2 6 3 7 2 6 7 6 7 5 1 3 2 2 3 2 3 3 1 5 6 7 4 6 3 [39] 2 7 > x[,1] [1] -0.62645381 0.18364332 -0.83562861 1.59528080 0.32950777 -0.82046838 [7] 0.48742905 0.73832471 0.57578135 -0.30538839 1.51178117 0.38984324 [13] -0.62124058 -2.21469989 1.12493092 -0.04493361 -0.01619026 0.94383621 [19] 0.82122120 0.59390132 0.91897737 0.78213630 0.07456498 -1.98935170 [25] 0.61982575 -0.05612874 -0.15579551 -1.47075238 -0.47815006 0.41794156 [31] 1.35867955 -0.10278773 0.38767161 -0.05380504 -1.37705956 -0.41499456 [37] -0.39428995 -0.05931340 1.10002537 0.76317575 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.