R version 4.2.0 (2022-04-22) -- "Vigorous Calisthenics"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
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'citation()' on how to cite R or R packages in publications.
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> if(!requireNamespace("quantreg") || !requireNamespace("KernSmooth")) q()
Loading required namespace: quantreg
Loading required namespace: KernSmooth
>
> ###################################################
> ### chunk number 1: setup
> ###################################################
> options(prompt = "R> ", continue = "+ ", width = 64,
+ digits = 4, show.signif.stars = FALSE, useFancyQuotes = FALSE)
R>
R> options(SweaveHooks = list(onefig = function() {par(mfrow = c(1,1))},
+ twofig = function() {par(mfrow = c(1,2))},
+ threefig = function() {par(mfrow = c(1,3))},
+ fourfig = function() {par(mfrow = c(2,2))},
+ sixfig = function() {par(mfrow = c(3,2))}))
R>
R> library("AER")
Loading required package: car
Loading required package: carData
Loading required package: lmtest
Loading required package: zoo
Attaching package: 'zoo'
The following objects are masked from 'package:base':
as.Date, as.Date.numeric
Loading required package: sandwich
Loading required package: survival
R>
R> suppressWarnings(RNGversion("3.5.0"))
R> set.seed(1071)
R>
R>
R> ###################################################
R> ### chunk number 2: journals-data
R> ###################################################
R> data("Journals", package = "AER")
R>
R>
R> ###################################################
R> ### chunk number 3: journals-dim
R> ###################################################
R> dim(Journals)
[1] 180 10
R> names(Journals)
[1] "title" "publisher" "society" "price"
[5] "pages" "charpp" "citations" "foundingyear"
[9] "subs" "field"
R>
R>
R> ###################################################
R> ### chunk number 4: journals-plot eval=FALSE
R> ###################################################
R> ## plot(log(subs) ~ log(price/citations), data = Journals)
R>
R>
R> ###################################################
R> ### chunk number 5: journals-lm eval=FALSE
R> ###################################################
R> ## j_lm <- lm(log(subs) ~ log(price/citations), data = Journals)
R> ## abline(j_lm)
R>
R>
R> ###################################################
R> ### chunk number 6: journals-lmplot
R> ###################################################
R> plot(log(subs) ~ log(price/citations), data = Journals)
R> j_lm <- lm(log(subs) ~ log(price/citations), data = Journals)
R> abline(j_lm)
R>
R>
R> ###################################################
R> ### chunk number 7: journals-lm-summary
R> ###################################################
R> summary(j_lm)
Call:
lm(formula = log(subs) ~ log(price/citations), data = Journals)
Residuals:
Min 1Q Median 3Q Max
-2.7248 -0.5361 0.0372 0.4662 1.8481
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.7662 0.0559 85.2 <2e-16
log(price/citations) -0.5331 0.0356 -15.0 <2e-16
Residual standard error: 0.75 on 178 degrees of freedom
Multiple R-squared: 0.557, Adjusted R-squared: 0.555
F-statistic: 224 on 1 and 178 DF, p-value: <2e-16
R>
R>
R> ###################################################
R> ### chunk number 8: cps-data
R> ###################################################
R> data("CPS1985", package = "AER")
R> cps <- CPS1985
R>
R>
R> ###################################################
R> ### chunk number 9: cps-data1 eval=FALSE
R> ###################################################
R> ## data("CPS1985", package = "AER")
R> ## cps <- CPS1985
R>
R>
R> ###################################################
R> ### chunk number 10: cps-reg
R> ###################################################
R> library("quantreg")
Loading required package: SparseM
Attaching package: 'SparseM'
The following object is masked from 'package:base':
backsolve
Attaching package: 'quantreg'
The following object is masked from 'package:survival':
untangle.specials
R> cps_lm <- lm(log(wage) ~ experience + I(experience^2) +
+ education, data = cps)
R> cps_rq <- rq(log(wage) ~ experience + I(experience^2) +
+ education, data = cps, tau = seq(0.2, 0.8, by = 0.15))
R>
R>
R> ###################################################
R> ### chunk number 11: cps-predict
R> ###################################################
R> cps2 <- data.frame(education = mean(cps$education),
+ experience = min(cps$experience):max(cps$experience))
R> cps2 <- cbind(cps2, predict(cps_lm, newdata = cps2,
+ interval = "prediction"))
R> cps2 <- cbind(cps2,
+ predict(cps_rq, newdata = cps2, type = ""))
R>
R>
R> ###################################################
R> ### chunk number 12: rq-plot eval=FALSE
R> ###################################################
R> ## plot(log(wage) ~ experience, data = cps)
R> ## for(i in 6:10) lines(cps2[,i] ~ experience,
R> ## data = cps2, col = "red")
R>
R>
R> ###################################################
R> ### chunk number 13: rq-plot1
R> ###################################################
R> plot(log(wage) ~ experience, data = cps)
R> for(i in 6:10) lines(cps2[,i] ~ experience,
+ data = cps2, col = "red")
R>
R>
R> ###################################################
R> ### chunk number 14: srq-plot eval=FALSE
R> ###################################################
R> ## plot(summary(cps_rq))
R>
R>
R> ###################################################
R> ### chunk number 15: srq-plot1
R> ###################################################
R> try(plot(summary(cps_rq)))
Warning messages:
1: In rq.fit.br(x, y, tau = tau, ci = TRUE, ...) :
Solution may be nonunique
2: In rq.fit.br(x, y, tau = tau, ci = TRUE, ...) :
Solution may be nonunique
R>
R>
R> ###################################################
R> ### chunk number 16: bkde-fit
R> ###################################################
R> library("KernSmooth")
KernSmooth 2.23 loaded
Copyright M. P. Wand 1997-2009
R> cps_bkde <- bkde2D(cbind(cps$experience, log(cps$wage)),
+ bandwidth = c(3.5, 0.5), gridsize = c(200, 200))
R>
R>
R> ###################################################
R> ### chunk number 17: bkde-plot eval=FALSE
R> ###################################################
R> ## image(cps_bkde$x1, cps_bkde$x2, cps_bkde$fhat,
R> ## col = rev(gray.colors(10, gamma = 1)),
R> ## xlab = "experience", ylab = "log(wage)")
R> ## box()
R> ## lines(fit ~ experience, data = cps2)
R> ## lines(lwr ~ experience, data = cps2, lty = 2)
R> ## lines(upr ~ experience, data = cps2, lty = 2)
R>
R>
R> ###################################################
R> ### chunk number 18: bkde-plot1
R> ###################################################
R> image(cps_bkde$x1, cps_bkde$x2, cps_bkde$fhat,
+ col = rev(gray.colors(10, gamma = 1)),
+ xlab = "experience", ylab = "log(wage)")
R> box()
R> lines(fit ~ experience, data = cps2)
R> lines(lwr ~ experience, data = cps2, lty = 2)
R> lines(upr ~ experience, data = cps2, lty = 2)
R>
R>
R> ###################################################
R> ### chunk number 19: install eval=FALSE
R> ###################################################
R> ## install.packages("AER")
R>
R>
R> ###################################################
R> ### chunk number 20: library
R> ###################################################
R> library("AER")
R>
R>
R> ###################################################
R> ### chunk number 21: objects
R> ###################################################
R> objects()
[1] "CPS1985" "Journals" "cps" "cps2" "cps_bkde"
[6] "cps_lm" "cps_rq" "i" "j_lm"
R>
R>
R> ###################################################
R> ### chunk number 22: search
R> ###################################################
R> search()
[1] ".GlobalEnv" "package:KernSmooth"
[3] "package:quantreg" "package:SparseM"
[5] "package:AER" "package:survival"
[7] "package:sandwich" "package:lmtest"
[9] "package:zoo" "package:car"
[11] "package:carData" "package:stats"
[13] "package:graphics" "package:grDevices"
[15] "package:utils" "package:datasets"
[17] "package:methods" "Autoloads"
[19] "package:base"
R>
R>
R> ###################################################
R> ### chunk number 23: assignment
R> ###################################################
R> x <- 2
R> objects()
[1] "CPS1985" "Journals" "cps" "cps2" "cps_bkde"
[6] "cps_lm" "cps_rq" "i" "j_lm" "x"
R>
R>
R> ###################################################
R> ### chunk number 24: remove
R> ###################################################
R> remove(x)
R> objects()
[1] "CPS1985" "Journals" "cps" "cps2" "cps_bkde"
[6] "cps_lm" "cps_rq" "i" "j_lm"
R>
R>
R> ###################################################
R> ### chunk number 25: log eval=FALSE
R> ###################################################
R> ## log(16, 2)
R> ## log(x = 16, 2)
R> ## log(16, base = 2)
R> ## log(base = 2, x = 16)
R>
R>
R> ###################################################
R> ### chunk number 26: q eval=FALSE
R> ###################################################
R> ## q()
R>
R>
R> ###################################################
R> ### chunk number 27: apropos
R> ###################################################
R> apropos("help")
[1] "help" "help.request" "help.search" "help.start"
R>
R>
R>
> proc.time()
user system elapsed
1.212 0.064 1.269
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