Commit 09daa8153f46f6a2c8d7d8879b718282db4b2e8d - effects

Import Debian changes 2.2.3-1 effects (2.2.3-1) unstable; urgency=low * New upstream release Dirk Eddelbuettel 5 years ago

10 changed file(s) with 89 addition(s) and 64 deletion(s). Raw diff Collapse all Expand all

-6

DESCRIPTION less more

0	0	Package: effects
1		Version: 2.2-2
2		Date: 2012/11/19
	1	Version: 2.2-3
	2	Date: 2012/12/10
3	3	Title: Effect Displays for Linear, Generalized Linear,
4	4	Multinomial-Logit, Proportional-Odds Logit Models and
5	5	Mixed-Effects Models

25	25	Maintainer: John Fox <jfox@mcmaster.ca>
26	26	Repository: CRAN
27	27	Repository/R-Forge/Project: effects
28		Repository/R-Forge/Revision: 96
29		Repository/R-Forge/DateTimeStamp: 2012-11-20 00:29:29
30		Date/Publication: 2012-11-21 19:45:42
31		Packaged: 2012-11-20 03:15:49 UTC; rforge
	28	Repository/R-Forge/Revision: 101
	29	Repository/R-Forge/DateTimeStamp: 2012-12-10 17:38:06
	30	Date/Publication: 2012-12-15 07:17:32
	31	Packaged: 2012-12-12 23:15:47 UTC; rforge

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MD5 less more

0		217aa30657981073adae73a138948377 *DESCRIPTION
1		4a4af07e42a9bee78d9c73c6e83363cc *NAMESPACE
2		79ee1d4a5fb94e708ed43a9574f6d9d2 *NEWS
3		6d07012714c54eedef0b36bdcc8b412e *R/Effect.R
4		1e7e6c304cb8a07bba60dd90a6ac3f38 *R/effects.R
	0	8d9e86ffc854065f6baf5773e6d9cce9 *DESCRIPTION
	1	c5dafda657fd2eacf8de7e455a399062 *NAMESPACE
	2	6b56d188b3365e02b9c4d367989b79f2 *NEWS
	3	dcb45113e2d60ee65afaa36d97f0a5f1 *R/Effect.R
	4	c0e3fe2c4f7ae3278f71a2d1da650d93 *R/effects.R
5	5	f40c347c6f473b310bba6a96de31db12 *R/effectsmer.R
6		1a41fb654905cc45d367696929bbdf4b *R/plot-summary-print-methods.R
7		3087dfa14f9b99b9fbfdb06c737cf1d6 *R/utilities.R
	6	96bae6d3a528a7aa76f569528c57ec39 *R/plot-summary-print-methods.R
	7	1afca09086376c02c8aa8f2a5d5e28a5 *R/utilities.R
8	8	7a5cb433347443c5faa00155458272be *data/Arrests.rda
9	9	1be79050796609a1cb71b2e8051c3624 *data/BEPS.rda
10	10	a50380d359a65c752f30e1fa441d9900 *data/Cowles.rda

25	25	18f83ed88afe8b1ecae2dbc3dc986b66 *man/Wells.Rd
26	26	54530a1709951eec94464f688647d735 *man/effect.Rd
27	27	03336c030e40258fc3316c4cb0c707d1 *man/effects-deprecated.Rd
28		57916854610b0cf37f32eeb8af9c392c *man/effects-package.Rd
	28	a39b1ed53c972b0101a3ff7e850fefe3 *man/effects-package.Rd
29	29	2ea5be34fc54d621a02e782cc81656ab *man/summary.effect.Rd

-1

NAMESPACE less more

0		# last modified 2012-09-06 by J. Fox
	0	# last modified 2012-11-30 by J. Fox
1	1
2	2	import(grid, lattice)
3	3	export(effect, allEffects, all.effects, Effect)

-0

NEWS less more

	0	Version 2.2-3
	1
	2	o Fixed bugs in axis scaling and xlim specification (reported by Achim Zeileis).
	3
	4	o Small changes for compatability with R 2.16.0.
	5
0	6	Version 2.2-2
1	7
2	8	o Use asymptotic normal to get confidence limits for mer and lme objects

-5

R/Effect.R less more

0	0	# Effect generic and methods
1	1	# John Fox and Sanford Weisberg
2		# last modified 2012-09-06 by J. Fox
	2	# last modified 2012-12-08 by J. Fox
3	3
4	4	Effect <- function(focal.predictors, mod, ...){
5	5	UseMethod("Effect", mod)

121	121	fit.1 <- na.omit(predict(mod))
122	122	mod.2 <- lm.fit(mod.matrix.all[1:nrow.X,], fit.1)
123	123	class(mod.2) <- "lm"
124		assign(".y", na.omit(model.response.gls(mod)), envir=.GlobalEnv)
125		assign(".X", na.omit(mod.matrix.all[1:nrow.X,]), envir=.GlobalEnv)
126		mod.3 <- update(mod, .y ~ .X - 1)
127		remove(".X", ".y", envir=.GlobalEnv)
	124	# assign(".y", na.omit(model.response.gls(mod)), envir=.GlobalEnv)
	125	# assign(".X", na.omit(mod.matrix.all[1:nrow.X,]), envir=.GlobalEnv)
	126	.Data <- list(.y=na.omit(model.response.gls(mod)), .X=na.omit(mod.matrix.all[1:nrow.X,]))
	127	mod.3 <- update(mod, .y ~ .X - 1, data=.Data)
	128	# remove(".X", ".y", envir=.GlobalEnv)
128	129	discrepancy <- 100*mean(abs(fitted(mod.2)- fit.1)/(1e-10 + mean(abs(fit.1))))
129	130	if (discrepancy > 1e-3) warning(paste("There is a discrepancy of", round(discrepancy, 3),
130	131	"percent \n in the 'safe' predictions used to generate effect", paste(focal.predictors, collapse="*")))

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R/effects.R less more

0	0	# effect generic and methods; allEffects
1		# John Fox and Jangman Hong
2		# last modified 2012-09-06 by J. Fox
	1	# John Fox, Sanford Weisberg, and Jangman Hong
	2	# last modified 2012-12-08 by J. Fox
3	3	# 10/31/2012 modifed effect.lm to use z distn for ses with mer and nlme objects
4	4
5	5	effect <- function(term, mod, ...){

215	215	fit.1 <- na.omit(predict(mod))
216	216	mod.2 <- lm.fit(mod.matrix.all[1:nrow.X,], fit.1)
217	217	class(mod.2) <- "lm"
218		assign(".y", na.omit(model.response.gls(mod)), envir=.GlobalEnv)
219		assign(".X", na.omit(mod.matrix.all[1:nrow.X,]), envir=.GlobalEnv)
220		mod.3 <- update(mod, .y ~ .X - 1)
221		remove(".X", ".y", envir=.GlobalEnv)
	218	# assign(".y", na.omit(model.response.gls(mod)), envir=.GlobalEnv)
	219	# assign(".X", na.omit(mod.matrix.all[1:nrow.X,]), envir=.GlobalEnv)
	220	.Data <- list(.y=na.omit(model.response.gls(mod)), .X=na.omit(mod.matrix.all[1:nrow.X,]))
	221	mod.3 <- update(mod, .y ~ .X - 1, data=.Data)
	222	# remove(".X", ".y", envir=.GlobalEnv)
222	223	discrepancy <- 100*mean(abs(fitted(mod.2)- fit.1)/(1e-10 + mean(abs(fit.1))))
223	224	if (discrepancy > 1e-3) warning(paste("There is a discrepancy of", round(discrepancy, 3),
224	225	"percent \n in the 'safe' predictions used to generate effect", term))

+46

-35

R/plot-summary-print-methods.R less more

0	0	# plot, summary, and print methods for effects package
1	1	# John Fox and Jangman Hong
2		# last modified 2012-11-06 by J. Fox
	2	# last modified 2012-11-30 by J. Fox
3	3	# 29 June 2011 added grid, rotx and roty arguments to the two plot methods
4	4	# by S. Weisberg
5	5

93	93	invisible(NULL)
94	94	}
95	95
96		# the following function isn't exported
	96	# the following two functions aren't exported
97	97
98	98	make.ticks <- function(range, link, inverse, at, n) {
	99	warn <- options(warn=-1)
	100	on.exit(warn)
99	101	link <- if (is.null(link))
100	102	function(x) nlm(function(y) (inverse(y) - x)^2,
101	103	mean(range))$estimate

106	108	}
107	109	else at
108	110	ticks <- sapply(labels, link)
109		list(at=ticks, labels=as.character(labels))
	111	list(at=ticks, labels=format(labels))
	112	}
	113
	114	range.adj <- function(x){
	115	range <- range(x)
	116	c(range[1] - .025*(range[2] - range[1]),
	117	range[2] + .025*(range[2] - range[1]))
110	118	}
111	119
112	120	# modified by Michael Friendly: added key.args:

120	128	transform.x=NULL, ticks.x=NULL,
121	129	key.args=NULL,
122	130	row=1, col=1, nrow=1, ncol=1, more=FALSE, ...){
123		make.ticks <- function(range, link, inverse, at, n) {
124		link <- if (is.null(link))
125		function(x) nlm(function(y) (inverse(y) - x)^2,
126		mean(range))$estimate
127		else link
128		if (is.null(n)) n <- 5
129		labels <- if (is.null(at)){
130		labels <- pretty(sapply(range, inverse), n=n+1)
131		}
132		else at
133		ticks <- sapply(labels, link)
134		list(at=ticks, labels=as.character(labels))
135		}
	131	# make.ticks <- function(range, link, inverse, at, n) {
	132	# link <- if (is.null(link))
	133	# function(x) nlm(function(y) (inverse(y) - x)^2,
	134	# mean(range))$estimate
	135	# else link
	136	# if (is.null(n)) n <- 5
	137	# labels <- if (is.null(at)){
	138	# labels <- pretty(sapply(range, inverse), n=n+1)
	139	# }
	140	# else at
	141	# ticks <- sapply(labels, link)
	142	# list(at=ticks, labels=format(labels))
	143	# }
136	144	type <- match.arg(type)
137	145	thresholds <- x$thresholds
138	146	has.thresholds <- !is.null(thresholds)

160	168	x.data <- x$data
161	169	effect <- paste(sapply(x$variables, "[[", "name"), collapse="*")
162	170	vars <- x$variables
163		x <- as.data.frame(x)
	171	x <- as.data.frame(x, transform=I)
164	172	for (i in 1:length(vars)){
165	173	if (!(vars[[i]]$is.factor)) next
166	174	x[,i] <- factor(x[,i], levels=vars[[i]]$levels)

210	218	else {
211	219	nm <- names(x)[1]
212	220	x.vals <- x.data[, nm]
213		if (nm %in% ticks.x){
	221	if (nm %in% names(ticks.x)){
214	222	at <- ticks.x[[nm]]$at
215	223	n <- ticks.x[[nm]]$n
216	224	}

218	226	at <- NULL
219	227	n <- 5
220	228	}
221		xlm <- if (nm %in% xlim){
	229	xlm <- if (nm %in% names(xlim)){
222	230	xlim[[nm]]
223	231	}
224		else range(x.vals)
	232	else range.adj(x[nm]) # range(x.vals)
225	233	tickmarks.x <- if ((nm %in% names(transform.x)) && !(is.null(transform.x))){
226	234	trans <- transform.x[[nm]]$trans
227	235	make.ticks(trans(xlm), link=transform.x[[nm]]$trans, inverse=transform.x[[nm]]$inverse, at=ticks.x$at, n=ticks.x$n)

250	258	}
251	259	},
252	260	ylim=ylim,
	261	xlim=trans(xlm),
253	262	ylab=ylab,
254	263	xlab=if (missing(xlab)) names(x)[1] else xlab,
255	264	x.vals=x.vals, rug=rug,

334	343	else{
335	344	nm <- names(x)[x.var]
336	345	x.vals <- x.data[, nm]
337		if (nm %in% ticks.x){
	346	if (nm %in% names(ticks.x)){
338	347	at <- ticks.x[[nm]]$at
339	348	n <- ticks.x[[nm]]$n
340	349	}

342	351	at <- NULL
343	352	n <- 5
344	353	}
345		xlm <- if (nm %in% xlim){
	354	xlm <- if (nm %in% names(xlim)){
346	355	xlim[[nm]]
347	356	}
348		else range(x.vals)
	357	else range.adj(x[nm]) # range(x.vals)
349	358	tickmarks.x <- if ((nm %in% names(transform.x)) && !(is.null(transform.x))){
350	359	trans <- transform.x[[nm]]$trans
351	360	make.ticks(trans(xlm), link=transform.x[[nm]]$trans, inverse=transform.x[[nm]]$inverse, at=ticks.x$at, n=ticks.x$n)

379	388	}
380	389	},
381	390	ylim=ylim,
	391	xlim=trans(xlm),
382	392	ylab=ylab,
383	393	xlab=if (missing(xlab)) predictors[x.var] else xlab,
384	394	x.vals=x.vals, rug=rug,

434	444	else{
435	445	nm <- names(x)[x.var]
436	446	x.vals <- x.data[, nm]
437		if (nm %in% ticks.x){
	447	if (nm %in% names(ticks.x)){
438	448	at <- ticks.x[[nm]]$at
439	449	n <- ticks.x[[nm]]$n
440	450	}

442	452	at <- NULL
443	453	n <- 5
444	454	}
445		xlm <- if (nm %in% xlim){
	455	xlm <- if (nm %in% names(xlim)){
446	456	xlim[[nm]]
447	457	}
448		else range(x.vals)
	458	else range.adj(x[nm]) # range(x.vals)
449	459	tickmarks.x <- if ((nm %in% names(transform.x)) && !(is.null(transform.x))){
450	460	trans <- transform.x[[nm]]$trans
451	461	make.ticks(trans(xlm), link=transform.x[[nm]]$trans, inverse=transform.x[[nm]]$inverse, at=ticks.x$at, n=ticks.x$n)

475	485	}
476	486	},
477	487	ylim=ylim,
	488	xlim=trans(xlm),
478	489	ylab=ylab,
479	490	xlab=if (missing(xlab)) predictors[x.var] else xlab,
480	491	x.vals=x.vals, rug=rug,

741	752	else { # x-variable numeric
742	753	nm <- predictors[x.var]
743	754	x.vals <- x$data[[nm]]
744		if (nm %in% ticks.x){
	755	if (nm %in% names(ticks.x)){
745	756	at <- ticks.x[[nm]]$at
746	757	n <- ticks.x[[nm]]$n
747	758	}

749	760	at <- NULL
750	761	n <- 5
751	762	}
752		xlm <- if (nm %in% xlim){
	763	xlm <- if (nm %in% names(xlim)){
753	764	xlim[[nm]]
754	765	}
755		else range(x.vals)
	766	else range.adj(data[nm]) # range(x.vals)
756	767	tickmarks.x <- if ((nm %in% names(transform.x)) && !(is.null(transform.x))){
757	768	trans <- transform.x[[nm]]$trans
758	769	make.ticks(trans(xlm), link=transform.x[[nm]]$trans, inverse=transform.x[[nm]]$inverse, at=ticks.x$at, n=ticks.x$n)

830	841	else { # x-variable numeric
831	842	nm <- predictors[x.var]
832	843	x.vals <- x$data[[nm]]
833		if (nm %in% ticks.x){
	844	if (nm %in% names(ticks.x)){
834	845	at <- ticks.x[[nm]]$at
835	846	n <- ticks.x[[nm]]$n
836	847	}

838	849	at <- NULL
839	850	n <- 5
840	851	}
841		xlm <- if (nm %in% xlim){
	852	xlm <- if (nm %in% names(xlim)){
842	853	xlim[[nm]]
843	854	}
844		else range(x.vals)
	855	else range.adj(data[nm]) # range(x.vals)
845	856	tickmarks.x <- if ((nm %in% names(transform.x)) && !(is.null(transform.x))){
846	857	trans <- transform.x[[nm]]$trans
847	858	make.ticks(trans(xlm), link=transform.x[[nm]]$trans, inverse=transform.x[[nm]]$inverse, at=ticks.x$at, n=ticks.x$n)

939	950	else { # x-variable numeric
940	951	nm <- predictors[x.var]
941	952	x.vals <- x$data[[nm]]
942		if (nm %in% ticks.x){
	953	if (nm %in% names(ticks.x)){
943	954	at <- ticks.x[[nm]]$at
944	955	n <- ticks.x[[nm]]$n
945	956	}

947	958	at <- NULL
948	959	n <- 5
949	960	}
950		xlm <- if (nm %in% xlim){
	961	xlm <- if (nm %in% names(xlim)){
951	962	xlim[[nm]]
952	963	}
953		else range(x.vals)
	964	else range.adj(data[nm]) # range(x.vals)
954	965	tickmarks.x <- if ((nm %in% names(transform.x)) && !(is.null(transform.x))){
955	966	trans <- transform.x[[nm]]$trans
956	967	make.ticks(trans(xlm), link=transform.x[[nm]]$trans, inverse=transform.x[[nm]]$inverse, at=ticks.x$at, n=ticks.x$n)

-1

R/utilities.R less more

1	1	# John Fox, Jangman Hong, and Sanford Weisberg
2	2	# last modified 2012-11-19 by J. Fox
3	3
4		if (getRversion() >= "2.15.1") globalVariables("wt")
	4	# if (getRversion() >= "2.15.1") globalVariables("wt")
5	5
6	6
7	7	has.intercept <- function(model, ...) any(names(coefficients(model))=="(Intercept)")

-0

debian/changelog less more

	0	effects (2.2.3-1) unstable; urgency=low
	1
	2	* New upstream release
	3
	4	-- Dirk Eddelbuettel <edd@debian.org> Mon, 24 Dec 2012 14:08:38 -0600
	5
0	6	effects (2.2.2-1) unstable; urgency=low
1	7
2	8	* New upstream release

-2

man/effects-package.Rd less more

14	14	\details{
15	15	\tabular{ll}{
16	16	Package: \tab effects\cr
17		Version: \tab 2.2-2\cr
18		Date: \tab 2012/11/06\cr
	17	Version: \tab 2.2-3\cr
	18	Date: \tab 2012/12/10\cr
19	19	Depends: \tab R (>= 2.4.0), lattice, grid, MASS, nnet, colorspace\cr
20	20	LazyLoad: \tab yes\cr
21	21	LazyData: \tab yes\cr