Mesmos resultados com Matlab R2015b:
mc'
ans = Columns 1 through 17 8.2834 7.7900 7.3243 7.8408 6.9411 8.0788 7.5859 8.5045 7.7377 7.6300 7.4584 8.3254 8.4231 9.2183 8.4298 8.1621 7.7530 Columns 18 through 34 8.5202 7.5397 8.4437 8.5259 8.5115 8.6919 7.8751 8.7256 8.4112 8.4320 8.0465 8.0767 7.6655 6.8035 7.0164 8.7062 7.7244 Columns 35 through 51 6.8070 6.9982 7.3664 7.2780 7.9291 7.8874 7.5017 6.7873 7.0532 7.3677 7.2136 7.2331 6.5543 7.7349 7.4804 7.8031 8.5610 Columns 52 through 68 7.7096 7.2965 7.4251 7.5591 7.4227 7.7352 7.4859 7.5243 7.4444 6.5160 6.2838 7.3013 6.7309 7.1362 6.7886 7.4702 7.3704 Columns 69 through 85 7.1180 7.1678 7.5752 7.1045 7.3966 7.1747 7.2116 7.4036 6.9948 7.1491 7.6249 6.7693 7.0764 7.1518 7.1104 7.7013 7.0376 Columns 86 through 102 6.8196 7.1667 7.5509 7.1804 6.8358 7.5356 6.3120 5.8329 5.8187 6.8354 6.5233 6.1144 7.1026 6.9876 5.8963 6.6491 6.1090 Columns 103 through 112 6.5956 6.6286 6.3461 6.5980 5.7874 6.3855 6.7979 6.1270 6.7997 6.4785
x'
ans = Columns 1 through 29 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 Columns 30 through 58 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 Columns 59 through 87 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 Columns 88 through 112 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380
myfun = 'mc ~ 9.548 - b1 * (x - 268)^b2'; b0 = [1;1]; mnl = fitnlm(x, mc, myfun, b0); mnl
mnl = Nonlinear regression model: mc ~ 9.548 - b1*(x - 268)^b2 Estimated Coefficients: Estimate SE tStat pValue ________ ________ ______ __________ b1 0.66888 0.10226 6.5412 1.9908e-09 b2 0.30739 0.036839 8.3441 2.3263e-13 Number of observations: 112, Error degrees of freedom: 110 Root Mean Squared Error: 0.541 R-Squared: 0.432, Adjusted R-Squared 0.427 F-statistic vs. zero model: 1.04e+04, p-value = 5.23e-126
model2 = 'mc ~ b1 - b2 * (x - 268)^b3'; ini2 = [8;0;1.4]; mnl2 = fitnlm(x, mc, model2, ini2);
Warning: Rank deficient, rank = 2, tol = 1.038937e-10. In nlinfit>LMfit (line 574) In nlinfit (line 276) In NonLinearModel/fitter (line 1123) In classreg.regr.FitObject/doFit (line 220) In NonLinearModel.fit (line 1430) In fitnlm (line 94)
mnl2
mnl2 = Nonlinear regression model: mc ~ b1 - b2*(x - 268)^b3 Estimated Coefficients: Estimate SE tStat pValue _________ _________ _______ __________ b1 8.0691 0.13723 58.802 2.1409e-84 b2 0.0021746 0.0035616 0.61058 0.54275 b3 1.4158 0.34368 4.1196 7.4165e-05 Number of observations: 112, Error degrees of freedom: 109 Root Mean Squared Error: 0.49 R-Squared: 0.537, Adjusted R-Squared 0.528 F-statistic vs. constant model: 63.2, p-value = 6e-19