File: Ch-Intro.Rout.save

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r-cran-aer 1.2-9-2
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R version 3.5.2 (2018-12-20) -- "Eggshell Igloo"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> ###################################################
> ### 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 
  1.441   0.069   1.493