R Markdown
d <- read.csv('overdue.txt',sep='')
head(d,n=5)
## LATE BILL
## 1 16 79
## 2 47 264
## 3 22 97
## 4 47 289
## 5 47 288
m<-lm(LATE~BILL,d)
summary(m)
##
## Call:
## lm(formula = LATE ~ BILL, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -45.846 -17.212 -0.793 19.007 47.774
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 51.98390 5.96405 8.716 9.84e-14 ***
## BILL -0.01264 0.03128 -0.404 0.687
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 23.72 on 94 degrees of freedom
## Multiple R-squared: 0.001734, Adjusted R-squared: -0.008885
## F-statistic: 0.1633 on 1 and 94 DF, p-value: 0.687
plot(d$BILL,d$LATE)
abline(m)
d$commercial[48:96] <- 1
d$commercial[1:48] <- 0
head(d,n=5)
## LATE BILL commercial
## 1 16 79 0
## 2 47 264 0
## 3 22 97 0
## 4 47 289 0
## 5 47 288 0
tail(d,n=5)
## LATE BILL commercial
## 92 47 288 1
## 93 55 225 1
## 94 86 79 1
## 95 94 46 1
## 96 59 215 1
m<-lm(LATE~.,d)
summary(m)
##
## Call:
## lm(formula = LATE ~ ., data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -27.7637 -11.4760 0.4037 12.4812 29.0765
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 33.28599 3.91286 8.507 2.93e-13 ***
## BILL -0.01264 0.01901 -0.665 0.508
## commercial 37.39583 2.94375 12.703 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 14.42 on 93 degrees of freedom
## Multiple R-squared: 0.635, Adjusted R-squared: 0.6272
## F-statistic: 80.91 on 2 and 93 DF, p-value: < 2.2e-16
plot(d$BILL,d$LATE)
abline(m)
## Warning in abline(m): only using the first two of 3 regression coefficients
m2<-lm(LATE~commercial*BILL,d)
summary(m2)
##
## Call:
## lm(formula = LATE ~ commercial * BILL, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -12.1211 -2.2163 0.0974 1.9556 8.6995
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.209624 1.198504 1.844 0.0685 .
## commercial 99.548561 1.694940 58.733 <2e-16 ***
## BILL 0.165683 0.006285 26.362 <2e-16 ***
## commercial:BILL -0.356644 0.008888 -40.125 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.371 on 92 degrees of freedom
## Multiple R-squared: 0.9803, Adjusted R-squared: 0.9796
## F-statistic: 1524 on 3 and 92 DF, p-value: < 2.2e-16
#plot(d$BILL,d$LATE)
#abline(m2)
(p<-predict(m2,d))
## 1 2 3 4 5 6 7 8
## 15.29858 45.94993 18.28087 50.09200 49.92632 18.77792 43.63037 25.40524
## 9 10 11 12 13 14 15 16
## 18.28087 51.74883 15.46426 53.73703 9.83104 20.43475 26.39934 35.51190
## 17 18 19 20 21 22 23 24
## 17.94951 36.17463 27.06207 28.38753 53.57135 34.84917 32.03256 26.89639
## 25 26 27 28 29 30 31 32
## 37.16873 17.12109 12.15060 33.19234 38.65988 13.80743 47.44108 10.49377
## 33 34 35 36 37 38 39 40
## 29.05027 27.55912 39.48829 37.00305 27.72480 37.83146 52.08020 41.97354
## 41 42 43 44 45 46 47 48
## 36.17463 17.94951 52.24588 18.44655 27.06207 31.86688 14.63585 35.18054
## 49 50 51 52 53 54 55 56
## 73.11396 46.57031 42.56012 44.66070 55.92743 67.57608 84.57165 83.61684
## 57 58 59 60 61 62 63 64
## 92.21011 86.48127 71.58627 80.75242 83.61684 59.74666 82.66204 61.46531
## 65 66 67 68 69 70 71 72
## 73.30492 62.61108 44.08781 88.39088 54.01781 63.37493 83.23492 83.04396
## 73 74 75 76 77 78 79 80
## 83.23492 72.54108 73.11396 73.87781 72.35012 64.13877 49.62570 62.61108
## 81 82 83 84 85 86 87 88
## 63.75685 90.30050 61.65627 87.43607 75.02358 66.04839 70.82242 42.36916
## 89 90 91 92 93 94 95 96
## 51.34435 67.38512 44.27878 46.76128 58.79185 86.67223 92.97396 60.70146
plot(d$BILL,p)
