Kết nối data
options(scipen=999)
library(readxl)
setwd("d:/DATA2020/HuongGian_FindModel")
dulieu <-read_excel("data.editor.SME.xlsx")
head(dulieu)
## # A tibble: 6 x 36
## Year Firm NHOM NS LnNS Labor LnLab IMS LnIMS ShortASS_old
## <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> <dbl>
## 1 2015 Kiml~ 1 14343 9.57 70 4.25 85 4.44 14603
## 2 2016 Kiml~ 1 35749 10.5 70 4.25 85.4 4.45 25637
## 3 2017 Kiml~ 1 57619 11.0 70 4.25 89 4.49 40326
## 4 2018 Kiml~ 1 58094 11.0 70 4.25 81.8 4.40 59317
## 5 2019 Kiml~ 1 82752 11.3 70 4.25 87 4.47 61195
## 6 2015 Wint~ 2 13441. 9.51 35 3.56 82.5 4.41 23974.
## # ... with 26 more variables: LongASS_old <dbl>, ShortLIA_old <dbl>,
## # LongLIA_old <dbl>, Equity_old <dbl>, ShortASS <dbl>, LongASS <dbl>,
## # ShortLIA <dbl>, LongLIA <dbl>, Equity <dbl>, LnSASS <dbl>, LnLASS <dbl>,
## # LnSLIA <dbl>, LnLLIA <dbl>, LnEQU <dbl>, ICTinf <dbl>, ICThum <dbl>,
## # ICTapp <dbl>, LnINF <dbl>, LnHUM <dbl>, LnAPP <dbl>, TRI <dbl>, ESS <dbl>,
## # GGDP <dbl>, LnESS <dbl>, LnGDP <dbl>, Dummy <dbl>
congthuc <- LnNS~ LnLab + LnIMS + ShortASS + LongASS + ShortLIA + LongLIA + Equity + ICTinf + ICThum + ICTapp + TRI + ESS + GGDP
congthuc1 <- LnNS~ LnLab + LnIMS + ShortASS + LongASS + ShortLIA + LongLIA + Equity + ICTinf + ICThum + ICTapp + TRI
congthuc2 <- LnNS~ LnLab + LnIMS + LnSASS + LnLASS+ LnSLIA + LnLLIA + Equity + ICTinf + ICThum + ICTapp + TRI
Hồi quy OLS
ols <-lm(congthuc,data=dulieu)
summary(ols)
##
## Call:
## lm(formula = congthuc, data = dulieu)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.0006 -0.7317 0.0395 0.6934 2.6575
##
## Coefficients: (2 not defined because of singularities)
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.18683 4.47372 -0.265 0.7909
## LnLab 0.49654 0.03736 13.290 <0.0000000000000002 ***
## LnIMS 1.44319 0.64315 2.244 0.0251 *
## ShortASS -0.81405 0.36708 -2.218 0.0269 *
## LongASS -0.78496 0.36729 -2.137 0.0329 *
## ShortLIA 0.83920 0.36705 2.286 0.0225 *
## LongLIA 0.80275 0.36739 2.185 0.0292 *
## Equity 0.79889 0.36710 2.176 0.0298 *
## ICTinf -3.84692 1.55732 -2.470 0.0137 *
## ICThum 5.63309 2.77793 2.028 0.0429 *
## ICTapp 2.69937 1.48038 1.823 0.0686 .
## TRI 0.02853 0.23307 0.122 0.9026
## ESS NA NA NA NA
## GGDP NA NA NA NA
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.096 on 809 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.5191, Adjusted R-squared: 0.5126
## F-statistic: 79.4 on 11 and 809 DF, p-value: < 0.00000000000000022
ols1 <- lm(congthuc1, data=dulieu)
summary(ols1)
##
## Call:
## lm(formula = congthuc1, data = dulieu)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.0006 -0.7317 0.0395 0.6934 2.6575
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.18683 4.47372 -0.265 0.7909
## LnLab 0.49654 0.03736 13.290 <0.0000000000000002 ***
## LnIMS 1.44319 0.64315 2.244 0.0251 *
## ShortASS -0.81405 0.36708 -2.218 0.0269 *
## LongASS -0.78496 0.36729 -2.137 0.0329 *
## ShortLIA 0.83920 0.36705 2.286 0.0225 *
## LongLIA 0.80275 0.36739 2.185 0.0292 *
## Equity 0.79889 0.36710 2.176 0.0298 *
## ICTinf -3.84692 1.55732 -2.470 0.0137 *
## ICThum 5.63309 2.77793 2.028 0.0429 *
## ICTapp 2.69937 1.48038 1.823 0.0686 .
## TRI 0.02853 0.23307 0.122 0.9026
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.096 on 809 degrees of freedom
## (4 observations deleted due to missingness)
## Multiple R-squared: 0.5191, Adjusted R-squared: 0.5126
## F-statistic: 79.4 on 11 and 809 DF, p-value: < 0.00000000000000022
phandu <-residuals(ols1)
# Phần dư có phân phối chuẩn
shapiro.test(phandu)
##
## Shapiro-Wilk normality test
##
## data: phandu
## W = 0.9961, p-value = 0.03824
# Kiểm tra đa cộng tuyến
library(car)
## Loading required package: carData
vif(ols1)
## LnLab LnIMS ShortASS LongASS ShortLIA LongLIA
## 1.712709 1.094830 74443.718555 4688.628703 49464.585363 1277.773248
## Equity ICTinf ICThum ICTapp TRI
## 9335.545086 6.756679 6.615243 20.520693 2.506939
ncvTest(ols1)
## Non-constant Variance Score Test
## Variance formula: ~ fitted.values
## Chisquare = 3.078924, Df = 1, p = 0.079313
library(lmtest)
## Loading required package: zoo
##
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric
bptest(ols1)
##
## studentized Breusch-Pagan test
##
## data: ols1
## BP = 39.358, df = 11, p-value = 0.00004605
durbinWatsonTest(ols1, max.lag = 4)
## lag Autocorrelation D-W Statistic p-value
## 1 0.7570721 0.4805085 0
## 2 0.5818561 0.8273130 0
## 3 0.4359441 1.1162726 0
## 4 0.3147961 1.3563408 0
## Alternative hypothesis: rho[lag] != 0
dwtest(ols1)
##
## Durbin-Watson test
##
## data: ols1
## DW = 0.48051, p-value < 0.00000000000000022
## alternative hypothesis: true autocorrelation is greater than 0
Hồi quy Ridge
library(lmridge)
##
## Attaching package: 'lmridge'
## The following object is masked from 'package:car':
##
## vif
so <-seq(0,0.1,by=.001)
ridge <-lmridge(congthuc1, data=dulieu, K=so)
vif(ridge)
## LnLab LnIMS ShortASS LongASS ShortLIA LongLIA
## k=0 1.71271 1.09483 74443.71856 4688.62870 49464.58537 1277.77325
## k=0.001 1.70189 1.08108 4.49850 6.06369 5.24472 2.92165
## k=0.002 1.69511 1.07843 1.65761 5.75191 3.30424 2.82517
## k=0.003 1.68838 1.07580 1.12208 5.59026 2.89755 2.76988
## k=0.004 1.68171 1.07320 0.92997 5.45505 2.72096 2.72211
## k=0.005 1.67508 1.07060 0.83759 5.33072 2.61247 2.67759
## k=0.006 1.66849 1.06803 0.78462 5.21323 2.53190 2.63522
## k=0.007 1.66196 1.06547 0.75037 5.10106 2.46543 2.59456
## k=0.008 1.65547 1.06293 0.72616 4.99347 2.40719 2.55540
## k=0.009 1.64902 1.06041 0.70784 4.89000 2.35437 2.51761
## k=0.01 1.64262 1.05790 0.69323 4.79033 2.30544 2.48109
## k=0.011 1.63626 1.05541 0.68109 4.69421 2.25949 2.44575
## k=0.012 1.62994 1.05293 0.67067 4.60143 2.21598 2.41154
## k=0.013 1.62367 1.05046 0.66148 4.51183 2.17453 2.37839
## k=0.014 1.61743 1.04801 0.65323 4.42523 2.13487 2.34625
## k=0.015 1.61124 1.04557 0.64568 4.34149 2.09680 2.31508
## k=0.016 1.60509 1.04314 0.63870 4.26047 2.06018 2.28483
## k=0.017 1.59897 1.04072 0.63217 4.18205 2.02488 2.25546
## k=0.018 1.59290 1.03832 0.62602 4.10611 1.99082 2.22694
## k=0.019 1.58686 1.03593 0.62018 4.03254 1.95790 2.19921
## k=0.02 1.58087 1.03355 0.61461 3.96124 1.92605 2.17226
## k=0.021 1.57491 1.03118 0.60927 3.89211 1.89522 2.14604
## k=0.022 1.56898 1.02882 0.60413 3.82505 1.86535 2.12053
## k=0.023 1.56310 1.02648 0.59917 3.75999 1.83638 2.09570
## k=0.024 1.55725 1.02414 0.59437 3.69684 1.80828 2.07153
## k=0.025 1.55144 1.02182 0.58972 3.63552 1.78101 2.04798
## k=0.026 1.54566 1.01950 0.58520 3.57596 1.75452 2.02503
## k=0.027 1.53992 1.01720 0.58081 3.51809 1.72878 2.00266
## k=0.028 1.53421 1.01490 0.57652 3.46184 1.70376 1.98085
## k=0.029 1.52854 1.01262 0.57234 3.40714 1.67943 1.95957
## k=0.03 1.52290 1.01034 0.56826 3.35395 1.65575 1.93881
## k=0.031 1.51729 1.00808 0.56427 3.30220 1.63271 1.91855
## k=0.032 1.51172 1.00582 0.56036 3.25184 1.61028 1.89877
## k=0.033 1.50618 1.00358 0.55654 3.20282 1.58843 1.87945
## k=0.034 1.50068 1.00134 0.55279 3.15508 1.56715 1.86057
## k=0.035 1.49520 0.99911 0.54911 3.10858 1.54641 1.84213
## k=0.036 1.48976 0.99690 0.54551 3.06328 1.52618 1.82410
## k=0.037 1.48435 0.99469 0.54197 3.01913 1.50646 1.80647
## k=0.038 1.47897 0.99249 0.53849 2.97609 1.48722 1.78923
## k=0.039 1.47363 0.99029 0.53508 2.93413 1.46845 1.77237
## k=0.04 1.46831 0.98811 0.53172 2.89320 1.45013 1.75586
## k=0.041 1.46303 0.98594 0.52842 2.85328 1.43224 1.73971
## k=0.042 1.45777 0.98377 0.52518 2.81432 1.41478 1.72389
## k=0.043 1.45255 0.98162 0.52198 2.77629 1.39771 1.70841
## k=0.044 1.44736 0.97947 0.51884 2.73916 1.38104 1.69324
## k=0.045 1.44219 0.97733 0.51574 2.70291 1.36475 1.67838
## k=0.046 1.43706 0.97520 0.51270 2.66750 1.34883 1.66381
## k=0.047 1.43195 0.97307 0.50969 2.63291 1.33325 1.64954
## k=0.048 1.42687 0.97096 0.50674 2.59911 1.31802 1.63554
## k=0.049 1.42183 0.96885 0.50382 2.56608 1.30313 1.62182
## k=0.05 1.41681 0.96675 0.50095 2.53378 1.28855 1.60836
## k=0.051 1.41181 0.96466 0.49812 2.50220 1.27429 1.59515
## k=0.052 1.40685 0.96257 0.49532 2.47132 1.26032 1.58220
## k=0.053 1.40191 0.96050 0.49257 2.44111 1.24666 1.56948
## k=0.054 1.39700 0.95843 0.48985 2.41155 1.23327 1.55700
## k=0.055 1.39212 0.95637 0.48717 2.38263 1.22016 1.54474
## k=0.056 1.38727 0.95431 0.48452 2.35432 1.20731 1.53271
## k=0.057 1.38244 0.95227 0.48191 2.32661 1.19473 1.52089
## k=0.058 1.37764 0.95023 0.47933 2.29948 1.18239 1.50928
## k=0.059 1.37287 0.94820 0.47679 2.27291 1.17031 1.49787
## k=0.06 1.36812 0.94618 0.47427 2.24688 1.15845 1.48666
## k=0.061 1.36339 0.94416 0.47179 2.22138 1.14683 1.47564
## k=0.062 1.35870 0.94215 0.46934 2.19640 1.13543 1.46481
## k=0.063 1.35403 0.94015 0.46692 2.17191 1.12425 1.45416
## k=0.064 1.34938 0.93816 0.46452 2.14791 1.11328 1.44369
## k=0.065 1.34476 0.93617 0.46216 2.12439 1.10252 1.43338
## k=0.066 1.34016 0.93419 0.45982 2.10132 1.09196 1.42325
## k=0.067 1.33559 0.93222 0.45751 2.07870 1.08159 1.41328
## k=0.068 1.33105 0.93025 0.45523 2.05651 1.07141 1.40347
## k=0.069 1.32652 0.92829 0.45297 2.03475 1.06142 1.39382
## k=0.07 1.32203 0.92634 0.45074 2.01339 1.05161 1.38432
## k=0.071 1.31755 0.92440 0.44854 1.99244 1.04197 1.37496
## k=0.072 1.31310 0.92246 0.44636 1.97188 1.03250 1.36576
## k=0.073 1.30867 0.92053 0.44420 1.95169 1.02319 1.35669
## k=0.074 1.30427 0.91860 0.44207 1.93188 1.01405 1.34775
## k=0.075 1.29989 0.91668 0.43996 1.91242 1.00507 1.33896
## k=0.076 1.29553 0.91477 0.43787 1.89331 0.99624 1.33029
## k=0.077 1.29120 0.91287 0.43581 1.87455 0.98756 1.32175
## k=0.078 1.28689 0.91097 0.43376 1.85612 0.97903 1.31334
## k=0.079 1.28260 0.90908 0.43174 1.83801 0.97063 1.30505
## k=0.08 1.27833 0.90719 0.42974 1.82022 0.96238 1.29687
## k=0.081 1.27409 0.90531 0.42776 1.80274 0.95427 1.28882
## k=0.082 1.26987 0.90344 0.42580 1.78556 0.94628 1.28087
## k=0.083 1.26567 0.90158 0.42386 1.76868 0.93843 1.27304
## k=0.084 1.26149 0.89972 0.42194 1.75208 0.93070 1.26532
## k=0.085 1.25733 0.89786 0.42004 1.73576 0.92309 1.25771
## k=0.086 1.25320 0.89602 0.41816 1.71971 0.91561 1.25019
## k=0.087 1.24909 0.89417 0.41630 1.70393 0.90824 1.24278
## k=0.088 1.24499 0.89234 0.41445 1.68841 0.90099 1.23547
## k=0.089 1.24092 0.89051 0.41263 1.67314 0.89384 1.22826
## k=0.09 1.23687 0.88869 0.41082 1.65812 0.88681 1.22114
## k=0.091 1.23284 0.88687 0.40903 1.64335 0.87989 1.21412
## k=0.092 1.22883 0.88506 0.40725 1.62881 0.87307 1.20718
## k=0.093 1.22484 0.88326 0.40549 1.61450 0.86635 1.20034
## k=0.094 1.22087 0.88146 0.40375 1.60042 0.85974 1.19359
## k=0.095 1.21693 0.87967 0.40203 1.58656 0.85322 1.18692
## k=0.096 1.21300 0.87788 0.40032 1.57292 0.84680 1.18033
## k=0.097 1.20909 0.87610 0.39863 1.55949 0.84047 1.17383
## k=0.098 1.20520 0.87433 0.39695 1.54626 0.83423 1.16741
## k=0.099 1.20133 0.87256 0.39529 1.53324 0.82808 1.16106
## k=0.1 1.19748 0.87080 0.39364 1.52041 0.82202 1.15480
## Equity ICTinf ICThum ICTapp TRI
## k=0 9335.54509 6.75668 6.61524 20.52069 2.50694
## k=0.001 6.85668 6.45808 6.27365 19.25722 2.44201
## k=0.002 6.35257 6.18584 5.97826 18.15190 2.39259
## k=0.003 6.14307 5.93563 5.70736 17.13978 2.34669
## k=0.004 5.98202 5.70505 5.45828 16.21065 2.30393
## k=0.005 5.83859 5.49202 5.22870 15.35569 2.26398
## k=0.006 5.70497 5.29474 5.01660 14.56720 2.22657
## k=0.007 5.57832 5.11162 4.82021 13.83846 2.19143
## k=0.008 5.45732 4.94127 4.63800 13.16358 2.15835
## k=0.009 5.34124 4.78248 4.46860 12.53738 2.12714
## k=0.01 5.22961 4.63417 4.31081 11.95530 2.09764
## k=0.011 5.12207 4.49539 4.16357 11.41327 2.06967
## k=0.012 5.01836 4.36528 4.02593 10.90770 2.04313
## k=0.013 4.91825 4.24311 3.89706 10.43540 2.01787
## k=0.014 4.82153 4.12818 3.77621 9.99350 1.99381
## k=0.015 4.72805 4.01991 3.66269 9.57946 1.97084
## k=0.016 4.63763 3.91776 3.55592 9.19097 1.94888
## k=0.017 4.55013 3.82122 3.45536 8.82598 1.92785
## k=0.018 4.46542 3.72988 3.36050 8.48263 1.90768
## k=0.019 4.38336 3.64332 3.27091 8.15923 1.88831
## k=0.02 4.30385 3.56120 3.18620 7.85428 1.86969
## k=0.021 4.22677 3.48319 3.10600 7.56639 1.85175
## k=0.022 4.15201 3.40899 3.02999 7.29431 1.83446
## k=0.023 4.07949 3.33834 2.95785 7.03691 1.81776
## k=0.024 4.00910 3.27098 2.88933 6.79314 1.80163
## k=0.025 3.94076 3.20671 2.82417 6.56207 1.78603
## k=0.026 3.87439 3.14530 2.76215 6.34282 1.77092
## k=0.027 3.80991 3.08658 2.70305 6.13460 1.75627
## k=0.028 3.74724 3.03036 2.64669 5.93668 1.74206
## k=0.029 3.68631 2.97650 2.59289 5.74839 1.72825
## k=0.03 3.62706 2.92485 2.54148 5.56912 1.71484
## k=0.031 3.56942 2.87527 2.49232 5.39830 1.70179
## k=0.032 3.51333 2.82764 2.44528 5.23541 1.68909
## k=0.033 3.45874 2.78184 2.40021 5.07996 1.67671
## k=0.034 3.40558 2.73777 2.35701 4.93151 1.66464
## k=0.035 3.35381 2.69533 2.31557 4.78963 1.65287
## k=0.036 3.30337 2.65443 2.27578 4.65396 1.64138
## k=0.037 3.25422 2.61498 2.23756 4.52413 1.63015
## k=0.038 3.20632 2.57691 2.20081 4.39980 1.61918
## k=0.039 3.15961 2.54013 2.16545 4.28068 1.60844
## k=0.04 3.11406 2.50459 2.13142 4.16648 1.59794
## k=0.041 3.06963 2.47022 2.09863 4.05693 1.58766
## k=0.042 3.02628 2.43696 2.06702 3.95177 1.57758
## k=0.043 2.98397 2.40476 2.03653 3.85078 1.56771
## k=0.044 2.94266 2.37355 2.00711 3.75374 1.55802
## k=0.045 2.90234 2.34330 1.97869 3.66045 1.54853
## k=0.046 2.86295 2.31396 1.95124 3.57071 1.53920
## k=0.047 2.82448 2.28548 1.92469 3.48435 1.53005
## k=0.048 2.78688 2.25783 1.89902 3.40119 1.52106
## k=0.049 2.75015 2.23096 1.87417 3.32109 1.51223
## k=0.05 2.71424 2.20485 1.85011 3.24389 1.50355
## k=0.051 2.67913 2.17945 1.82680 3.16945 1.49501
## k=0.052 2.64479 2.15474 1.80421 3.09765 1.48661
## k=0.053 2.61121 2.13069 1.78230 3.02836 1.47835
## k=0.054 2.57836 2.10727 1.76104 2.96147 1.47021
## k=0.055 2.54622 2.08444 1.74041 2.89686 1.46220
## k=0.056 2.51476 2.06220 1.72037 2.83443 1.45432
## k=0.057 2.48397 2.04051 1.70090 2.77409 1.44654
## k=0.058 2.45382 2.01935 1.68199 2.71574 1.43889
## k=0.059 2.42430 1.99870 1.66359 2.65930 1.43134
## k=0.06 2.39539 1.97854 1.64570 2.60468 1.42390
## k=0.061 2.36706 1.95885 1.62828 2.55180 1.41656
## k=0.062 2.33932 1.93962 1.61133 2.50060 1.40932
## k=0.063 2.31213 1.92082 1.59483 2.45100 1.40218
## k=0.064 2.28548 1.90244 1.57874 2.40294 1.39513
## k=0.065 2.25936 1.88447 1.56307 2.35634 1.38818
## k=0.066 2.23375 1.86688 1.54779 2.31116 1.38131
## k=0.067 2.20864 1.84967 1.53288 2.26734 1.37453
## k=0.068 2.18402 1.83283 1.51834 2.22482 1.36783
## k=0.069 2.15987 1.81633 1.50415 2.18355 1.36122
## k=0.07 2.13617 1.80017 1.49030 2.14348 1.35468
## k=0.071 2.11292 1.78434 1.47677 2.10457 1.34822
## k=0.072 2.09011 1.76882 1.46355 2.06677 1.34184
## k=0.073 2.06772 1.75361 1.45063 2.03004 1.33553
## k=0.074 2.04574 1.73869 1.43800 1.99434 1.32929
## k=0.075 2.02416 1.72406 1.42566 1.95963 1.32312
## k=0.076 2.00298 1.70970 1.41358 1.92588 1.31702
## k=0.077 1.98218 1.69561 1.40177 1.89304 1.31099
## k=0.078 1.96174 1.68178 1.39021 1.86110 1.30502
## k=0.079 1.94167 1.66820 1.37889 1.83000 1.29912
## k=0.08 1.92196 1.65486 1.36781 1.79974 1.29328
## k=0.081 1.90258 1.64176 1.35695 1.77026 1.28750
## k=0.082 1.88355 1.62889 1.34632 1.74156 1.28178
## k=0.083 1.86484 1.61624 1.33590 1.71359 1.27611
## k=0.084 1.84645 1.60381 1.32568 1.68634 1.27051
## k=0.085 1.82838 1.59159 1.31567 1.65979 1.26496
## k=0.086 1.81060 1.57956 1.30585 1.63390 1.25946
## k=0.087 1.79313 1.56774 1.29621 1.60866 1.25402
## k=0.088 1.77595 1.55611 1.28676 1.58404 1.24863
## k=0.089 1.75905 1.54467 1.27749 1.56002 1.24329
## k=0.09 1.74242 1.53341 1.26838 1.53659 1.23801
## k=0.091 1.72607 1.52232 1.25944 1.51373 1.23277
## k=0.092 1.70998 1.51141 1.25066 1.49141 1.22758
## k=0.093 1.69415 1.50066 1.24204 1.46962 1.22244
## k=0.094 1.67857 1.49008 1.23357 1.44835 1.21734
## k=0.095 1.66324 1.47966 1.22525 1.42757 1.21229
## k=0.096 1.64815 1.46939 1.21707 1.40727 1.20729
## k=0.097 1.63330 1.45927 1.20903 1.38744 1.20233
## k=0.098 1.61868 1.44930 1.20112 1.36806 1.19741
## k=0.099 1.60428 1.43948 1.19335 1.34912 1.19254
## k=0.1 1.59010 1.42979 1.18570 1.33061 1.18771
# Xem kết quả
rstats1(ridge) ->chonMSE
chonMSE
##
## Ridge Regression Statistics 1:
##
## Variance Bias^2 MSE rsigma2 F R2 adj-R2 CN
## K=0 167036.5266 0.0 167036.5 1.1995 79.4991 0.5191 0.5132 550612.1666
## K=0.001 75.6982 824218.3 824293.9 1.2054 79.1131 0.5154 0.5094 3928.5663
## K=0.002 66.7510 830129.6 830196.4 1.2055 79.1089 0.5146 0.5086 1971.8122
## K=0.003 63.1889 832114.9 832178.1 1.2055 79.1056 0.5138 0.5078 1316.4442
## K=0.004 60.5714 833110.9 833171.4 1.2056 79.1020 0.5131 0.5071 988.1728
## K=0.005 58.3322 833710.0 833768.3 1.2056 79.0979 0.5124 0.5064 791.0215
## K=0.006 56.3202 834110.3 834166.7 1.2057 79.0934 0.5117 0.5056 659.5087
## K=0.007 54.4757 834397.1 834451.5 1.2058 79.0884 0.5110 0.5050 565.5325
## K=0.008 52.7674 834612.7 834665.5 1.2059 79.0830 0.5103 0.5043 495.0293
## K=0.009 51.1758 834781.0 834832.2 1.2059 79.0772 0.5097 0.5036 440.1809
## K=0.01 49.6866 834916.2 834965.9 1.2060 79.0711 0.5090 0.5029 396.2943
## K=0.011 48.2892 835027.2 835075.5 1.2061 79.0647 0.5084 0.5023 360.3819
## K=0.012 46.9745 835120.2 835167.1 1.2062 79.0581 0.5077 0.5017 330.4514
## K=0.013 45.7350 835199.2 835244.9 1.2063 79.0512 0.5071 0.5010 305.1230
## K=0.014 44.5643 835267.3 835311.8 1.2065 79.0440 0.5065 0.5004 283.4110
## K=0.015 43.4567 835326.6 835370.0 1.2066 79.0368 0.5059 0.4998 264.5926
## K=0.016 42.4070 835378.8 835421.2 1.2067 79.0293 0.5053 0.4992 248.1255
## K=0.017 41.4110 835425.2 835466.6 1.2068 79.0217 0.5047 0.4986 233.5948
## K=0.018 40.4645 835466.6 835507.1 1.2069 79.0139 0.5042 0.4980 220.6781
## K=0.019 39.5639 835504.0 835543.6 1.2070 79.0061 0.5036 0.4975 209.1204
## K=0.02 38.7060 835537.8 835576.6 1.2072 78.9981 0.5030 0.4969 198.7181
## K=0.021 37.8878 835568.7 835606.6 1.2073 78.9900 0.5025 0.4963 189.3062
## K=0.022 37.1067 835596.9 835634.0 1.2074 78.9819 0.5019 0.4958 180.7496
## K=0.023 36.3602 835622.9 835659.3 1.2075 78.9736 0.5014 0.4952 172.9369
## K=0.024 35.6459 835646.9 835682.6 1.2077 78.9653 0.5008 0.4947 165.7750
## K=0.025 34.9620 835669.2 835704.1 1.2078 78.9569 0.5003 0.4941 159.1859
## K=0.026 34.3065 835689.9 835724.2 1.2079 78.9486 0.4998 0.4936 153.1035
## K=0.027 33.6777 835709.2 835742.8 1.2080 78.9401 0.4992 0.4931 147.4715
## K=0.028 33.0739 835727.2 835760.3 1.2082 78.9315 0.4987 0.4925 142.2417
## K=0.029 32.4937 835744.2 835776.7 1.2083 78.9230 0.4982 0.4920 137.3725
## K=0.03 31.9358 835760.2 835792.1 1.2084 78.9144 0.4977 0.4915 132.8279
## K=0.031 31.3989 835775.2 835806.6 1.2086 78.9058 0.4972 0.4910 128.5763
## K=0.032 30.8817 835789.5 835820.3 1.2087 78.8972 0.4967 0.4905 124.5905
## K=0.033 30.3834 835802.9 835833.3 1.2088 78.8885 0.4962 0.4900 120.8461
## K=0.034 29.9027 835815.7 835845.6 1.2090 78.8798 0.4957 0.4895 117.3220
## K=0.035 29.4389 835827.9 835857.3 1.2091 78.8711 0.4952 0.4890 113.9992
## K=0.036 28.9910 835839.5 835868.5 1.2092 78.8624 0.4947 0.4885 110.8609
## K=0.037 28.5582 835850.5 835879.1 1.2094 78.8536 0.4942 0.4880 107.8923
## K=0.038 28.1397 835861.1 835889.2 1.2095 78.8449 0.4938 0.4875 105.0799
## K=0.039 27.7349 835871.1 835898.9 1.2096 78.8361 0.4933 0.4870 102.4117
## K=0.04 27.3431 835880.8 835908.2 1.2098 78.8273 0.4928 0.4865 99.8768
## K=0.041 26.9636 835890.1 835917.0 1.2099 78.8186 0.4923 0.4861 97.4656
## K=0.042 26.5959 835899.0 835925.6 1.2100 78.8098 0.4919 0.4856 95.1692
## K=0.043 26.2394 835907.5 835933.8 1.2102 78.8010 0.4914 0.4851 92.9796
## K=0.044 25.8936 835915.8 835941.7 1.2103 78.7922 0.4909 0.4847 90.8895
## K=0.045 25.5581 835923.7 835949.3 1.2104 78.7834 0.4905 0.4842 88.8923
## K=0.046 25.2323 835931.4 835956.6 1.2106 78.7746 0.4900 0.4837 86.9819
## K=0.047 24.9159 835938.7 835963.7 1.2107 78.7658 0.4896 0.4833 85.1527
## K=0.048 24.6084 835945.9 835970.5 1.2109 78.7570 0.4891 0.4828 83.3998
## K=0.049 24.3095 835952.8 835977.1 1.2110 78.7482 0.4887 0.4824 81.7184
## K=0.05 24.0188 835959.4 835983.5 1.2111 78.7393 0.4882 0.4819 80.1043
## K=0.051 23.7359 835965.9 835989.6 1.2113 78.7305 0.4878 0.4815 78.5535
## K=0.052 23.4606 835972.2 835995.6 1.2114 78.7217 0.4873 0.4810 77.0622
## K=0.053 23.1925 835978.2 836001.4 1.2115 78.7129 0.4869 0.4806 75.6273
## K=0.054 22.9313 835984.1 836007.1 1.2117 78.7042 0.4865 0.4801 74.2455
## K=0.055 22.6768 835989.8 836012.5 1.2118 78.6953 0.4860 0.4797 72.9139
## K=0.056 22.4287 835995.4 836017.8 1.2119 78.6866 0.4856 0.4793 71.6299
## K=0.057 22.1868 836000.8 836023.0 1.2121 78.6778 0.4852 0.4788 70.3910
## K=0.058 21.9508 836006.1 836028.0 1.2122 78.6690 0.4847 0.4784 69.1947
## K=0.059 21.7205 836011.2 836032.9 1.2123 78.6602 0.4843 0.4780 68.0390
## K=0.06 21.4957 836016.2 836037.7 1.2125 78.6514 0.4839 0.4775 66.9218
## K=0.061 21.2762 836021.0 836042.3 1.2126 78.6426 0.4835 0.4771 65.8413
## K=0.062 21.0618 836025.8 836046.8 1.2127 78.6339 0.4831 0.4767 64.7956
## K=0.063 20.8523 836030.4 836051.2 1.2129 78.6251 0.4826 0.4762 63.7831
## K=0.064 20.6476 836034.9 836055.5 1.2130 78.6163 0.4822 0.4758 62.8022
## K=0.065 20.4475 836039.3 836059.7 1.2132 78.6075 0.4818 0.4754 61.8515
## K=0.066 20.2517 836043.6 836063.8 1.2133 78.5988 0.4814 0.4750 60.9296
## K=0.067 20.0603 836047.8 836067.8 1.2134 78.5900 0.4810 0.4746 60.0352
## K=0.068 19.8730 836051.9 836071.7 1.2136 78.5813 0.4806 0.4742 59.1671
## K=0.069 19.6896 836055.9 836075.6 1.2137 78.5725 0.4802 0.4737 58.3242
## K=0.07 19.5102 836059.8 836079.3 1.2138 78.5638 0.4798 0.4733 57.5054
## K=0.071 19.3344 836063.6 836083.0 1.2140 78.5550 0.4794 0.4729 56.7096
## K=0.072 19.1623 836067.4 836086.6 1.2141 78.5463 0.4790 0.4725 55.9360
## K=0.073 18.9937 836071.1 836090.1 1.2142 78.5376 0.4786 0.4721 55.1835
## K=0.074 18.8284 836074.7 836093.5 1.2144 78.5289 0.4782 0.4717 54.4513
## K=0.075 18.6665 836078.2 836096.9 1.2145 78.5201 0.4778 0.4713 53.7387
## K=0.076 18.5077 836081.7 836100.2 1.2146 78.5114 0.4774 0.4709 53.0449
## K=0.077 18.3520 836085.1 836103.4 1.2148 78.5027 0.4770 0.4705 52.3690
## K=0.078 18.1993 836088.4 836106.6 1.2149 78.4940 0.4766 0.4701 51.7105
## K=0.079 18.0495 836091.6 836109.7 1.2150 78.4853 0.4762 0.4697 51.0687
## K=0.08 17.9025 836094.8 836112.7 1.2152 78.4766 0.4758 0.4693 50.4429
## K=0.081 17.7582 836098.0 836115.7 1.2153 78.4679 0.4754 0.4689 49.8325
## K=0.082 17.6166 836101.1 836118.7 1.2154 78.4592 0.4750 0.4685 49.2370
## K=0.083 17.4776 836104.1 836121.6 1.2156 78.4505 0.4746 0.4681 48.6559
## K=0.084 17.3410 836107.1 836124.4 1.2157 78.4418 0.4742 0.4678 48.0886
## K=0.085 17.2069 836110.0 836127.2 1.2159 78.4332 0.4739 0.4674 47.5347
## K=0.086 17.0752 836112.9 836130.0 1.2160 78.4245 0.4735 0.4670 46.9936
## K=0.087 16.9457 836115.7 836132.7 1.2161 78.4158 0.4731 0.4666 46.4650
## K=0.088 16.8185 836118.5 836135.3 1.2163 78.4072 0.4727 0.4662 45.9484
## K=0.089 16.6935 836121.2 836137.9 1.2164 78.3985 0.4723 0.4658 45.4434
## K=0.09 16.5706 836123.9 836140.5 1.2165 78.3898 0.4720 0.4655 44.9496
## K=0.091 16.4497 836126.5 836143.0 1.2167 78.3812 0.4716 0.4651 44.4667
## K=0.092 16.3309 836129.1 836145.5 1.2168 78.3725 0.4712 0.4647 43.9943
## K=0.093 16.2140 836131.7 836147.9 1.2169 78.3639 0.4708 0.4643 43.5320
## K=0.094 16.0990 836134.2 836150.3 1.2171 78.3552 0.4705 0.4639 43.0796
## K=0.095 15.9858 836136.7 836152.7 1.2172 78.3466 0.4701 0.4636 42.6367
## K=0.096 15.8745 836139.2 836155.0 1.2173 78.3379 0.4697 0.4632 42.2030
## K=0.097 15.7649 836141.6 836157.3 1.2175 78.3293 0.4694 0.4628 41.7783
## K=0.098 15.6570 836143.9 836159.6 1.2176 78.3207 0.4690 0.4625 41.3622
## K=0.099 15.5508 836146.3 836161.8 1.2177 78.3120 0.4686 0.4621 40.9545
## K=0.1 15.4463 836148.6 836164.0 1.2179 78.3034 0.4683 0.4617 40.5550
min(chonMSE$mse)
## [1] 167036.5
infocr(ridge) -> chonAIC
chonAIC
## AIC BIC
## K=0 160.3029 5721.458
## K=0.001 163.1988 5719.409
## K=0.002 163.1369 5719.073
## K=0.003 163.0712 5718.754
## K=0.004 163.0135 5718.455
## K=0.005 162.9656 5718.175
## K=0.006 162.9268 5717.912
## K=0.007 162.8969 5717.666
## K=0.008 162.8747 5717.434
## K=0.009 162.8599 5717.217
## K=0.01 162.8516 5717.011
## K=0.011 162.8490 5716.817
## K=0.012 162.8520 5716.634
## K=0.013 162.8596 5716.461
## K=0.014 162.8721 5716.297
## K=0.015 162.8884 5716.142
## K=0.016 162.9085 5715.994
## K=0.017 162.9320 5715.854
## K=0.018 162.9585 5715.721
## K=0.019 162.9880 5715.594
## K=0.02 163.0203 5715.474
## K=0.021 163.0545 5715.358
## K=0.022 163.0915 5715.249
## K=0.023 163.1306 5715.145
## K=0.024 163.1713 5715.045
## K=0.025 163.2142 5714.951
## K=0.026 163.2579 5714.858
## K=0.027 163.3041 5714.773
## K=0.028 163.3515 5714.691
## K=0.029 163.4002 5714.611
## K=0.03 163.4500 5714.535
## K=0.031 163.5009 5714.463
## K=0.032 163.5530 5714.393
## K=0.033 163.6060 5714.326
## K=0.034 163.6605 5714.264
## K=0.035 163.7156 5714.204
## K=0.036 163.7714 5714.146
## K=0.037 163.8284 5714.091
## K=0.038 163.8857 5714.038
## K=0.039 163.9440 5713.987
## K=0.04 164.0028 5713.939
## K=0.041 164.0621 5713.892
## K=0.042 164.1224 5713.848
## K=0.043 164.1831 5713.806
## K=0.044 164.2442 5713.765
## K=0.045 164.3057 5713.726
## K=0.046 164.3683 5713.691
## K=0.047 164.4312 5713.656
## K=0.048 164.4942 5713.622
## K=0.049 164.5578 5713.591
## K=0.05 164.6222 5713.562
## K=0.051 164.6867 5713.534
## K=0.052 164.7512 5713.506
## K=0.053 164.8163 5713.480
## K=0.054 164.8816 5713.456
## K=0.055 164.9478 5713.434
## K=0.056 165.0138 5713.412
## K=0.057 165.0803 5713.392
## K=0.058 165.1471 5713.373
## K=0.059 165.2141 5713.355
## K=0.06 165.2817 5713.339
## K=0.061 165.3488 5713.322
## K=0.062 165.4167 5713.308
## K=0.063 165.4847 5713.295
## K=0.064 165.5532 5713.283
## K=0.065 165.6219 5713.272
## K=0.066 165.6903 5713.261
## K=0.067 165.7595 5713.252
## K=0.068 165.8287 5713.244
## K=0.069 165.8980 5713.236
## K=0.07 165.9673 5713.229
## K=0.071 166.0375 5713.225
## K=0.072 166.1073 5713.219
## K=0.073 166.1775 5713.216
## K=0.074 166.2474 5713.211
## K=0.075 166.3182 5713.210
## K=0.076 166.3887 5713.208
## K=0.077 166.4596 5713.208
## K=0.078 166.5307 5713.209
## K=0.079 166.6016 5713.209
## K=0.08 166.6731 5713.211
## K=0.081 166.7447 5713.214
## K=0.082 166.8160 5713.216
## K=0.083 166.8880 5713.221
## K=0.084 166.9600 5713.225
## K=0.085 167.0315 5713.229
## K=0.086 167.1039 5713.235
## K=0.087 167.1761 5713.242
## K=0.088 167.2482 5713.248
## K=0.089 167.3207 5713.255
## K=0.09 167.3936 5713.264
## K=0.091 167.4661 5713.272
## K=0.092 167.5390 5713.282
## K=0.093 167.6121 5713.292
## K=0.094 167.6852 5713.303
## K=0.095 167.7584 5713.314
## K=0.096 167.8317 5713.325
## K=0.097 167.9052 5713.338
## K=0.098 167.9787 5713.350
## K=0.099 168.0524 5713.364
## K=0.1 168.1263 5713.378
Ước lượng Rigde tối ưu
ridge01 <- lmridge(congthuc1, data=dulieu, K=0.03)
summary(ridge01)
##
## Call:
## lmridge.default(formula = congthuc1, data = dulieu, K = 0.03)
##
##
## Coefficients: for Ridge parameter K= 0.03
## Estimate Estimate (Sc) StdErr (Sc) t-value (Sc) Pr(>|t|)
## Intercept 1.4676 -233.9751 23.6102 -9.9099 <0.0000000000000002
## LnLab 0.4717 18.1070 1.3566 13.3474 <0.0000000000000002
## LnIMS 1.3623 2.4290 1.1050 2.1982 0.0282
## ShortASS 0.0070 5.6974 0.8287 6.8752 <0.0000000000000002
## LongASS 0.0272 5.5507 2.0132 2.7571 0.0060
## ShortLIA 0.0161 10.6829 1.4145 7.5523 <0.0000000000000002
## LongLIA -0.0070 -0.7499 1.5307 -0.4899 0.6243
## Equity -0.0120 -3.4466 2.0936 -1.6463 0.1001
## ICTinf -2.4284 -4.4421 1.8800 -2.3628 0.0184
## ICThum 3.3564 3.4057 1.7525 1.9434 0.0523
## ICTapp 1.3340 4.4734 2.5942 1.7244 0.0850
## TRI -0.0529 -0.3937 1.4395 -0.2735 0.7845
##
## Intercept ***
## LnLab ***
## LnIMS *
## ShortASS ***
## LongASS **
## ShortLIA ***
## LongLIA
## Equity
## ICTinf *
## ICThum .
## ICTapp .
## TRI
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Ridge Summary
## R2 adj-R2 DF ridge F AIC BIC
## 0.49770 0.49150 8.86227 78.91441 163.44995 5714.53535
## Ridge minimum MSE= 835792.1 at K= 0.03
## P-value for F-test ( 8.86227 , 811.3449 ) = 0.000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000185442
## -------------------------------------------------------------------
vif(ridge01)
## LnLab LnIMS ShortASS LongASS ShortLIA LongLIA Equity ICTinf ICThum
## k=0.03 1.5229 1.01034 0.56826 3.35395 1.65575 1.93881 3.62706 2.92485 2.54148
## ICTapp TRI
## k=0.03 5.56912 1.71484