# UNIVERSIDAD NACIONAL DEL ALTIPLANO
# INGENIERIA ESTADISTICA E INFORMATICA
# CURSO: SERIES DE TIEMPO
library(readxl)
## Warning: package 'readxl' was built under R version 4.0.2
library(lubridate)
## Warning: package 'lubridate' was built under R version 4.0.5
##
## Attaching package: 'lubridate'
## The following objects are masked from 'package:base':
##
## date, intersect, setdiff, union
library(tidyverse)
## Warning: package 'tidyverse' was built under R version 4.0.5
## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --
## v ggplot2 3.3.3 v purrr 0.3.4
## v tibble 3.1.5 v dplyr 1.0.7
## v tidyr 1.1.4 v stringr 1.4.0
## v readr 2.0.2 v forcats 0.5.1
## Warning: package 'ggplot2' was built under R version 4.0.3
## Warning: package 'tibble' was built under R version 4.0.5
## Warning: package 'tidyr' was built under R version 4.0.5
## Warning: package 'readr' was built under R version 4.0.5
## Warning: package 'dplyr' was built under R version 4.0.5
## Warning: package 'forcats' was built under R version 4.0.5
## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x lubridate::as.difftime() masks base::as.difftime()
## x lubridate::date() masks base::date()
## x dplyr::filter() masks stats::filter()
## x lubridate::intersect() masks base::intersect()
## x dplyr::lag() masks stats::lag()
## x lubridate::setdiff() masks base::setdiff()
## x lubridate::union() masks base::union()
library(car)
## Warning: package 'car' was built under R version 4.0.5
## Loading required package: carData
##
## Attaching package: 'car'
## The following object is masked from 'package:dplyr':
##
## recode
## The following object is masked from 'package:purrr':
##
## some
library(tseries)
## Warning: package 'tseries' was built under R version 4.0.5
## Registered S3 method overwritten by 'quantmod':
## method from
## as.zoo.data.frame zoo
library(astsa)
## Warning: package 'astsa' was built under R version 4.0.5
library(foreign)
## Warning: package 'foreign' was built under R version 4.0.3
library(timsac)
## Warning: package 'timsac' was built under R version 4.0.3
library(vars)
## Warning: package 'vars' was built under R version 4.0.5
## Loading required package: MASS
##
## Attaching package: 'MASS'
## The following object is masked from 'package:dplyr':
##
## select
## Loading required package: strucchange
## Warning: package 'strucchange' was built under R version 4.0.5
## Loading required package: zoo
##
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric
## Loading required package: sandwich
##
## Attaching package: 'strucchange'
## The following object is masked from 'package:stringr':
##
## boundary
## Loading required package: urca
## Warning: package 'urca' was built under R version 4.0.5
## Loading required package: lmtest
## Warning: package 'lmtest' was built under R version 4.0.2
library(lmtest)
library(mFilter)
## Warning: package 'mFilter' was built under R version 4.0.5
library(dynlm)
## Warning: package 'dynlm' was built under R version 4.0.5
library(nlme)
## Warning: package 'nlme' was built under R version 4.0.5
##
## Attaching package: 'nlme'
## The following object is masked from 'package:dplyr':
##
## collapse
library(broom)
## Warning: package 'broom' was built under R version 4.0.5
library(kableExtra)
## Warning: package 'kableExtra' was built under R version 4.0.5
##
## Attaching package: 'kableExtra'
## The following object is masked from 'package:dplyr':
##
## group_rows
library(knitr)
library(MASS)
library(parallel)
library(car)
library(mlogit)
## Warning: package 'mlogit' was built under R version 4.0.5
## Loading required package: dfidx
## Warning: package 'dfidx' was built under R version 4.0.5
##
## Attaching package: 'dfidx'
## The following object is masked from 'package:MASS':
##
## select
## The following object is masked from 'package:stats':
##
## filter
library(dplyr)
library(tidyr)
library(forecast)
## Warning: package 'forecast' was built under R version 4.0.5
##
## Attaching package: 'forecast'
## The following object is masked from 'package:nlme':
##
## getResponse
## The following object is masked from 'package:astsa':
##
## gas
library(fpp2)
## Warning: package 'fpp2' was built under R version 4.0.5
## -- Attaching packages ---------------------------------------------- fpp2 2.4 --
## v fma 2.4 v expsmooth 2.3
## Warning: package 'fma' was built under R version 4.0.5
## Warning: package 'expsmooth' was built under R version 4.0.5
## -- Conflicts ------------------------------------------------- fpp2_conflicts --
## x forecast::getResponse() masks nlme::getResponse()
## x car::some() masks purrr::some()
##
## Attaching package: 'fpp2'
## The following object is masked from 'package:astsa':
##
## oil
library(stats)
library(quantmod)
## Warning: package 'quantmod' was built under R version 4.0.5
## Loading required package: xts
## Warning: package 'xts' was built under R version 4.0.5
##
## Attaching package: 'xts'
## The following objects are masked from 'package:dplyr':
##
## first, last
## Loading required package: TTR
INFLACION <- read_excel("E:/SERIES DE TIEMPO/TAREA 03/INFLACION.xls")
attach(INFLACION)
names(INFLACION)
## [1] "Periodo" "INDICEG"
inflacion <- ts(INFLACION$INDICEG, start = c(1970,1),frequency = 12)
plot(inflacion, main = "Inflacion en Mexico", col = "blue")
#Modelos Autoregresivos de Orden 1 (Consumo)
modelo1 <- dynlm(inflacion~L(inflacion), data = INFLACION)
#Modelos Autoregresivos de Orden 3
modelo2 <- dynlm(inflacion~L(inflacion,1:3),data = INFLACION)
#Modelos Autoregresivos con rezagos multiples
modelo3 <- dynlm(inflacion~L(inflacion, c(1,3,5)),data = INFLACION)
#Generar la Variable Tendencia
tend=seq_along(inflacion)
tend
## [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
## [19] 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36
## [37] 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54
## [55] 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72
## [73] 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90
## [91] 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108
## [109] 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126
## [127] 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144
## [145] 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162
## [163] 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180
## [181] 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198
## [199] 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216
## [217] 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234
## [235] 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252
## [253] 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270
## [271] 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288
## [289] 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306
## [307] 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324
## [325] 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342
## [343] 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360
## [361] 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378
## [379] 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396
## [397] 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414
## [415] 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432
## [433] 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450
## [451] 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468
## [469] 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486
## [487] 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504
## [505] 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522
## [523] 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540
## [541] 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558
## [559] 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576
## [577] 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594
## [595] 595
#Agregar tendencia al modelo Regresion
modelo4 <- dynlm(inflacion~L(inflacion, c(1,3,5)) + tend,data = INFLACION)#trend(inflacion)
summary(modelo4)
##
## Time series regression with "ts" data:
## Start = 1970(6), End = 2019(7)
##
## Call:
## dynlm(formula = inflacion ~ L(inflacion, c(1, 3, 5)) + tend,
## data = INFLACION)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.6528 -0.3500 -0.0786 0.2243 7.4912
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2967793 0.1012594 2.931 0.00351 **
## L(inflacion, c(1, 3, 5))1 0.7593185 0.0321612 23.610 < 2e-16 ***
## L(inflacion, c(1, 3, 5))3 0.0764182 0.0364587 2.096 0.03651 *
## L(inflacion, c(1, 3, 5))5 0.0696191 0.0320499 2.172 0.03024 *
## tend -0.0004948 0.0002464 -2.008 0.04513 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9333 on 585 degrees of freedom
## Multiple R-squared: 0.7941, Adjusted R-squared: 0.7927
## F-statistic: 564 on 4 and 585 DF, p-value: < 2.2e-16
#Agregar Estacionalidad al modelo Regresion
modelo5 <- dynlm(inflacion~L(inflacion, c(1,3,5))+trend(inflacion) + season(inflacion),data = INFLACION)
summary(modelo5)
##
## Time series regression with "ts" data:
## Start = 1970(6), End = 2019(7)
##
## Call:
## dynlm(formula = inflacion ~ L(inflacion, c(1, 3, 5)) + trend(inflacion) +
## season(inflacion), data = INFLACION)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.0669 -0.3448 -0.0342 0.2368 6.9837
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.938800 0.154206 6.088 2.09e-09 ***
## L(inflacion, c(1, 3, 5))1 0.751504 0.032744 22.951 < 2e-16 ***
## L(inflacion, c(1, 3, 5))3 0.102611 0.036594 2.804 0.005217 **
## L(inflacion, c(1, 3, 5))5 0.065226 0.032595 2.001 0.045849 *
## trend(inflacion) -0.005014 0.002749 -1.824 0.068697 .
## season(inflacion)Feb -1.413851 0.175729 -8.046 4.94e-15 ***
## season(inflacion)Mar -0.884642 0.178473 -4.957 9.45e-07 ***
## season(inflacion)Apr -0.855764 0.183638 -4.660 3.93e-06 ***
## season(inflacion)May -1.174847 0.178281 -6.590 9.98e-11 ***
## season(inflacion)Jun -0.673700 0.183319 -3.675 0.000260 ***
## season(inflacion)Jul -0.700015 0.176661 -3.962 8.35e-05 ***
## season(inflacion)Aug -0.516337 0.176372 -2.928 0.003552 **
## season(inflacion)Sep -0.747915 0.175798 -4.254 2.45e-05 ***
## season(inflacion)Oct -0.647694 0.176068 -3.679 0.000257 ***
## season(inflacion)Nov -0.403294 0.176428 -2.286 0.022625 *
## season(inflacion)Dec -0.226236 0.175317 -1.290 0.197417
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.8657 on 574 degrees of freedom
## Multiple R-squared: 0.8261, Adjusted R-squared: 0.8216
## F-statistic: 181.8 on 15 and 574 DF, p-value: < 2.2e-16