[r-cran-zelig] 03/102: Import Upstream version 2.0-13
Andreas Tille
tille at debian.org
Sun Jan 8 16:58:08 UTC 2017
This is an automated email from the git hooks/post-receive script.
tille pushed a commit to branch master
in repository r-cran-zelig.
commit a689949d0718c18e35756e8173d1cdf9242d25f0
Author: Andreas Tille <tille at debian.org>
Date: Sun Jan 8 09:38:57 2017 +0100
Import Upstream version 2.0-13
---
DESCRIPTION | 6 ++---
R/dims.R | 6 +++++
R/plot.zelig.beta.R | 12 +++++++++
R/print.relogit.R | 44 ++++++++++++++++----------------
R/rocplot.R | 48 ++++++++++++++++++++---------------
README | 10 ++++++++
man/dims.Rd | 41 ++++++++++++++++++++++++++++++
man/rocplot.Rd | 72 +++++++++++++++++++++++++++++++----------------------
8 files changed, 165 insertions(+), 74 deletions(-)
diff --git a/DESCRIPTION b/DESCRIPTION
index 4fb69fe..a6b3f6d 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
Package: Zelig
-Version: 2.0-11
-Date: 2005-01-14
+Version: 2.0-13
+Date: 2005-03-11
Title: Zelig: Everyone's Statistical Software
Author: Kosuke Imai <kimai at Princeton.Edu>,
Gary King <king at harvard.edu>,
@@ -22,4 +22,4 @@ Description: Zelig is an easy-to-use program that can estimate, and
translates them into quantities of direct interest.
License: GPL version 2 or newer
URL: http://gking.harvard.edu/zelig
-Packaged: Fri Jan 14 15:04:05 2005; king
+Packaged: Fri Mar 11 11:04:06 2005; king
diff --git a/R/dims.R b/R/dims.R
new file mode 100644
index 0000000..6cbae0a
--- /dev/null
+++ b/R/dims.R
@@ -0,0 +1,6 @@
+dims <- function(x) {
+ if (is.vector(x))
+ return(length(x))
+ else
+ return(dim(x))
+}
diff --git a/R/plot.zelig.beta.R b/R/plot.zelig.beta.R
new file mode 100644
index 0000000..a392bd4
--- /dev/null
+++ b/R/plot.zelig.beta.R
@@ -0,0 +1,12 @@
+plot.zelig.beta <- function(x, xlab = "", user.par = FALSE, alt.col = "red", ...){
+ k <- length(x$qi)
+ op <- par(no.readonly = TRUE)
+ if (!user.par)
+ par(mar = c(4,4,2,1), tcl = -0.25, mgp = c(2, 0.6, 0))
+ par(mfrow = c(k, 1))
+ for (i in 1:k) {
+ qi <- as.vector(x$qi[[i]])
+ plot(density(qi), main = x$qi.name[[i]], xlab = xlab, ...)
+ }
+ par(op)
+}
diff --git a/R/print.relogit.R b/R/print.relogit.R
index d6b7944..433e233 100644
--- a/R/print.relogit.R
+++ b/R/print.relogit.R
@@ -1,26 +1,28 @@
-print.relogit <-function (x, digits = max(3, getOption("digits") - 3),
+print.relogit <- function(x, digits = max(3, getOption("digits") - 3),
...) {
if (is.null(x$call$bias.correct))
x$call$bias.correct <- TRUE
cat("\nCall: ", deparse(x$call), "\n\n")
- cat("Coefficients")
- if (is.character(co <- x$contrasts))
- cat(" [contrasts: ", apply(cbind(names(co), co),
- 1, paste, collapse = "="), "]")
- cat(":\n")
- print.default(format(x$coefficients, digits = digits),
- print.gap = 2, quote = FALSE)
- if (!is.null(x$call$tau)) {
- cat("\nIntercepts with prior correction for: \n")
- print.default(x$correct, digits = digits,
- print.gap = 1, quote = FALSE)
- }
- cat("\nDegrees of Freedom:", x$df.null, "Total (i.e. Null); ",
- x$df.residual, "Residual\n")
- cat("Null Deviance:\t ", format(signif(x$null.deviance,
- digits)), "\nResidual Deviance:", format(signif(x$deviance,
- digits)), "\tAIC:", format(signif(x$aic, digits)), "\n")
- if (x$call$bias.correct)
- cat("Rare events bias correction performed.")
- invisible(x)
+ cat("Coefficients")
+ if (is.character(co <- x$contrasts))
+ cat(" [contrasts: ", apply(cbind(names(co), co),
+ 1, paste, collapse = "="), "]")
+ cat(":\n")
+ print.default(format(x$coefficients, digits = digits),
+ print.gap = 2, quote = FALSE)
+ if (!is.null(x$call$tau)) {
+ cat("\nIntercepts with prior correction for: \n")
+ print.default(x$correct, digits = digits,
+ print.gap = 1, quote = FALSE)
+ }
+ cat("\nDegrees of Freedom:", x$df.null, "Total (i.e. Null); ",
+ x$df.residual, "Residual\n")
+ cat("Null Deviance:\t ", format(signif(x$null.deviance,
+ digits)),
+ "\nResidual Deviance:", format(signif(x$deviance,
+ digits)),
+ "\tAIC:", format(signif(x$aic, digits)), "\n")
+ if (x$call$bias.correct)
+ cat("Rare events bias correction performed.\n")
+ invisible(x)
}
diff --git a/R/rocplot.R b/R/rocplot.R
index 57b3418..14e0a45 100644
--- a/R/rocplot.R
+++ b/R/rocplot.R
@@ -3,22 +3,36 @@ rocplot <- function(y1, y2, fitted1, fitted2,
lty2="dashed", lwd1=par("lwd"), lwd2=par("lwd"),
col1=par("col"), col2=par("col"), main="ROC Curve",
xlab = "Proportion of 1's Correctly Predicted",
- ylab="Proportion of 0's Correctly Predicted", ...) {
- op <- par(no.readonly = TRUE)
- par(mar = c(4,4,2,1), tcl = -0.25, mgp = c(2, 0.6, 0))
- ones <- zeros <- matrix(NA, nrow = length(cutoff), ncol = 2)
+ ylab="Proportion of 0's Correctly Predicted", plot = TRUE, ...) {
+ roc1 <- roc2 <- matrix(NA, nrow = length(cutoff), ncol = 2)
+ colnames(roc1) <- colnames(roc2) <- c("ones", "zeros")
for (i in 1:length(cutoff)) {
- ones[i,1] <- mean(fitted1[y1==1] >= cutoff[i])
- ones[i,2] <- mean(fitted2[y2==1] >= cutoff[i])
- zeros[i,1] <- mean(fitted1[y1==0] < cutoff[i])
- zeros[i,2] <- mean(fitted2[y2==0] < cutoff[i])
+ roc1[i,1] <- mean(fitted1[y1==1] >= cutoff[i])
+ roc2[i,1] <- mean(fitted2[y2==1] >= cutoff[i])
+ roc1[i,2] <- mean(fitted1[y1==0] < cutoff[i])
+ roc2[i,2] <- mean(fitted2[y2==0] < cutoff[i])
+ }
+ if (plot) {
+ op <- par(no.readonly = TRUE)
+ par(mar = c(4,4,2,1), tcl = -0.25, mgp = c(2, 0.6, 0))
+ plot(0:1, 0:1, type = "n", xaxs = "i", yaxs = "i",
+ main=main, xlab=xlab, ylab=ylab, ...)
+ lines(roc1, lty = lty1, lwd = lwd1, col=col1)
+ lines(roc2, lty = lty2, lwd = lwd2, col=col2)
+ abline(1, -1, lty = "dotted")
+ par(op)
+ }
+ else {
+ area1 <- area2 <- array()
+ for (i in 2:length(cutoff)) {
+ area1[i-1] <- (roc1[i,2] - roc1[(i-1),2]) * roc1[i,1]
+ area2[i-1] <- (roc2[i,2] - roc2[(i-1),2]) * roc2[i,1]
+ }
+ return(list(roc1 = roc1,
+ roc2 = roc2,
+ area1 = sum(na.omit(area1)),
+ area2 = sum(na.omit(area2))))
}
- plot(0:1, 0:1, type = "n", xaxs = "i", yaxs = "i",
- main=main, xlab=xlab, ylab=ylab, ...)
- lines(cbind(ones[,1], zeros[,1]), lty = lty1, lwd = lwd1, col=col1)
- lines(cbind(ones[,2], zeros[,2]), lty = lty2, lwd = lwd2, col=col2)
- abline(1, -1, lty = "dotted")
- par(op)
}
@@ -30,9 +44,3 @@ rocplot <- function(y1, y2, fitted1, fitted2,
-
-
-
-
-
-
diff --git a/README b/README
index c7a3e98..9fe82d9 100644
--- a/README
+++ b/README
@@ -1,3 +1,13 @@
+2.0-13 (March 11, 2005): Stable release for R 1.9.1-2.0.1. Fixed bugs in
+ NAMESPACE and rocplot.Rd.
+
+2.0-12 (February 20, 2005): Stable release for R 1.9.1-2.0.1. Added plot
+ = TRUE option to rocplot().
+
+2.0-11 (January 14, 2005): Stable release for R 1.9.1-2.0.1. Changed
+ class name for subsettted models from "multiple" to "strata", and
+ modified affected functions.
+
2.0-10 (January 4, 2005): Stable release for R 1.9.1 and R 2.0.0. Fixed
bug in simulation procedure for ordinal logit. (Reported by Ian Yohai.)
diff --git a/man/dims.Rd b/man/dims.Rd
new file mode 100644
index 0000000..5a68f2e
--- /dev/null
+++ b/man/dims.Rd
@@ -0,0 +1,41 @@
+\name{dims}
+
+\alias{dims}
+
+\title{Return Dimensions of Vectors, Arrays, and Data Frames}
+
+\description{
+ Retrieve or set the dimensions of a vector, array, or data frame.
+}
+
+\usage{
+dims(x)
+dims(x) <- value
+}
+
+\arguments{
+ \item{x}{An R object. For example, a vector, matrix, array, or data
+frame.}
+ \item{value}{For the default method, either \code{NULL} or a numeric
+vector coerced to integer (by truncation).}
+}
+
+\value{
+ The function \code{dims} performs exactly the same as \code{dim}, and
+additionally returns the \code{length} of vectors (treating them as
+one-dimensional arrays).}
+
+\seealso{\code{dim}, \code{length}}
+
+\author{ Olivia Lau <\email{olau at fas.harvard.edu}>
+}
+
+\examples{
+a <- 1:12
+dims(a)
+
+a <- matrix(1, nrow = 4, ncol = 9)
+dims(a)
+}
+
+\keyword{file}
diff --git a/man/rocplot.Rd b/man/rocplot.Rd
index 0f03e49..ddafe80 100644
--- a/man/rocplot.Rd
+++ b/man/rocplot.Rd
@@ -7,57 +7,69 @@
\title{Receiver Operator Characteristic Plots}
-\description{
-The \code{rocplot} command generates a receiver operator
-characteristic plot to compare the in-sample (default) or
-out-of-sample fit for two logit or probit regressions.
-}
+\description{ The \code{rocplot} command generates a receiver operator
+characteristic plot to compare the in-sample (default) or out-of-sample
+fit for two logit or probit regressions. }
\usage{
rocplot(y1, y2, fitted1, fitted2, cutoff = seq(from=0, to=1, length=100),
lty1 = "solid", lty2 = "dashed", lwd1 = par("lwd"), lwd2 = par("lwd"),
- col1 = par("col"), col2 = par("col"), main, xlab, ylab, ...)
+ col1 = par("col"), col2 = par("col"), main, xlab, ylab,
+ plot = TRUE, ...)
}
\arguments{
-\item{y1}{Response variable for the first model. }
-\item{y2}{Response variable for the second model. }
+\item{y1}{Response variable for the first model.}
+\item{y2}{Response variable for the second model.}
\item{fitted1}{Fitted values for the first model. These values
- may represent either the in-sample or out-of-sample fitted values. }
-\item{fitted2}{Fitted values for the second model. }
+ may represent either the in-sample or out-of-sample fitted values.}
+\item{fitted2}{Fitted values for the second model.}
\item{cutoff}{A vector of cut-off values between 0 and 1, at
which to evaluate the proportion of 0s and 1s correctly predicted by
the first and second model. By default, this is 100 increments
- between 0 and 1, inclusive. }
-\item{lty1, lty2}{The line type for the first model ({\tt
- lty1}) and the second model (\code{lty2}), defaulting to solid and
- dashed, respectively. }
-\item{lwd1, lwd2}{The width of the line for the first
- model (\code{lwd1}) and the second model (\code{lwd2}), defaulting to
- 1 for both. }
+ between 0 and 1, inclusive.}
+\item{lty1, lty2}{The line type for the first model (\code{lty1}) and
+ the second model (\code{lty2}), defaulting to solid and dashed,
+ respectively.}
+\item{lwd1, lwd2}{The width of the line for the first model
+ (\code{lwd1}) and the second model (\code{lwd2}), defaulting to 1 for both.}
\item{col1, col2}{The colors of the line for the first
model (\code{col1}) and the second model (\code{col2}), defaulting to
- black for both. }
-\item{main}{a title for the plot. Defaults to "Roc Curve".}
-\item{xlab}{a label for the x-axis. Defaults to "Proportion of 1's
-Correctly Predicted".}
-\item{ylab}{a label for the y-axis. Defaults to Proportion of 0's
-Correctly Predicted".}
+ black for both.}
+\item{main}{a title for the plot. Defaults to \code{ROC Curve}.}
+\item{xlab}{a label for the x-axis. Defaults to \code{Proportion of 1's
+ Correctly Predicted}.}
+\item{ylab}{a label for the y-axis. Defaults to \code{Proportion of 0's
+ Correctly Predicted}.}
+\item{plot}{defaults to \code{TRUE}, which generates a plot to the
+ selected device. If \code{FALSE}, returns a list of
+items (see below).}
\item{\dots}{Additional parameters passed to plot, including
\code{xlab}, \code{ylab}, and \code{main}. }
}
-\value{
-For two logit or probit models, \code{rocplot} returns an on-screen
-window with the desired ROC plot.
+\value{ If \code{plot = TRUE}, \code{rocplot} generates an ROC plot for
+two logit or probit models. If \code{plot = FALSE}, \code{rocplot}
+returns a list with the following elements: {
+ \item{roc1}{a matrix containing a vector of x-coordinates and
+ y-coordinates corresponding to the number of ones and zeros correctly
+ predicted for the first model.}
+ \item{roc2}{a matrix containing a vector of x-coordinates and
+ y-coordinates corresponding to the number of ones and zeros correctly
+ predicted for the second model.}
+ \item{area1}{the area under the first ROC curve, calculated using
+ Reimann sums.}
+ \item{area2}{the area under the second ROC curve, calculated using
+ Reimann sums.}
+}
}
-\example{
+\examples{
data(turnout)
z.out1 <- zelig(vote ~ race + educate + age, model = "logit",
- data = turnout)
+ data = turnout)
z.out2 <- zelig(vote ~ race + educate, model = "logit",
- data = turnout)
+ data = turnout)
rocplot(z.out1$y, z.out2$y, fitted(z.out1), fitted(z.out2))
}
@@ -69,4 +81,4 @@ rocplot(z.out1$y, z.out2$y, fitted(z.out1), fitted(z.out2))
<\email{king at harvard.edu}>; Olivia Lau <\email{olau at fas.harvard.edu}>
}
-\keyword{aplot}
+\keyword{file}
--
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