similar to: lm() and dffits

Displaying 16 results from an estimated 16 matches similar to: "lm() and dffits"

2008 Oct 19
2
definition of "dffits"
R-users E-mail: r-help@r-project.org Hi! R-users. I am just wondering what the definition of "dffits" in R language is. Let me show you an simple example. function() { library(MASS) xx <- c(1,2,3,4,5) yy <- c(1,3,4,2,4) data1 <- data.frame(x=xx, y=yy) lm.out <- lm(y~., data=data1, x=T) lev1 <- lm.influence(lm.out)$hat sig1 <-
2006 Aug 31
1
NaN when using dffits, stemming from lm.influence call
Hi all I'm getting a NaN returned on using dffits, as explained below. To me, there seems no obvious (or non-obvious reason for that matter) reason why a NaN appears. Before I start digging further, can anyone see why dffits might be failing? Is there a problem with the data? Consider: # Load data dep <-
2005 Jun 27
1
delta-beta's
Hi there I have created a multivariate logistic regression model looking at the presence/absence of disease on farms. I would like to plot the diagnostic plots recommended by Hosmer & Lemeshow to look particularly for any points of high influence. In order to do this I need to extract values for delta-beta. The function dfbeta gives a value for change in each coefficient but I am looking
2010 Feb 21
1
tests for measures of influence in regression
influence.measures gives several measures of influence for each observation (Cook's Distance, etc) and actually flags observations that it determines are influential by any of the measures. Looks good! But how does it discriminate between the influential and non- influential observations by each of the measures? Like does it do a Bonferroni-corrected t on the residuals identified by
2013 Dec 02
1
pamer.fnc y la nueva versión de R
Hace unos meses os escribir para comunicaros que había un fallo en esta función. Como os prometí os comento la respuesta por si alguno está interesado en utilizar el paquete LMERconvenientsfucntions Dear Javier, The package has been updated and should work for you fine now. Note that function mcp.fnc does not return the fourth plot (dffits) anymore. We still have to figure out a way to compute
2012 Feb 15
1
influence.measures()
Hi dear all, I'm wondering about the question that; Does the influence.measures(model) for linear models valid for general linear models such as logistic regression models? That is; If I fit the model like model <- glm( y~X1+X2, family=binomial) Then, if i apply the function "influence.measures(model), i will get the result of influence measures. These result are valid for
2017 Apr 04
0
Some "lm" methods give wrong results when applied to "mlm" objects
I had a look at some influence measures, and it seems to me that currently several methods handle multiple lm (mlm) objects wrongly in R. In some cases there are separate "mlm" methods, but usually "mlm" objects are handled by the same methods as univariate "lm" methods, and in some cases this fails. There are two general patterns of problems in influence measures:
2009 Aug 03
0
Deducer 0.1 : An intuitive cross-platform data analysis GUI
Deducer 0.1 has been released to CRAN Deducer is designed to be a free, easy to use, alternative to proprietary software such as SPSS, JMP, and Minitab. It has a menu system to do common data manipulation and data analysis tasks, and an excel-like spreadsheet in which to view and edit data frames. The goal of the project is to two fold. 1. Provide an intuitive interface so that non-technical
2009 Aug 03
0
Deducer 0.1 : An intuitive cross-platform data analysis GUI
Deducer 0.1 has been released to CRAN Deducer is designed to be a free, easy to use, alternative to proprietary software such as SPSS, JMP, and Minitab. It has a menu system to do common data manipulation and data analysis tasks, and an excel-like spreadsheet in which to view and edit data frames. The goal of the project is to two fold. 1. Provide an intuitive interface so that non-technical
2010 Oct 06
2
A problem --thank you
dear:teacher i have a problem which about the polr()(package "MASS"), if the response must have 3 or more levels? and how to fit the polr() to 2 levels? thank you. turly yours [[alternative HTML version deleted]]
2003 Nov 23
3
make check reg-tests-3
Should I submit this as a bug report? --- reg-tests-3.Rout.save Thu Jul 3 09:55:40 2003 +++ reg-tests-3.Rout Sun Nov 23 13:10:57 2003 @@ -1,17 +1,18 @@ -R : Copyright 2003, The R Development Core Team -Version 1.8.0 Under development (unstable) (2003-07-03) +R : Copyright 2003, The R Foundation for Statistical Computing +Version 1.8.1 (2003-11-21), ISBN 3-900051-00-3 R is free software and
2000 Feb 07
2
R-0.99.0 is released
I've rolled up R-0.99.0.tgz a moment ago. You can get it from ftp://cvs.r-project.org/pub/CRAN/src/base/R-0.99.0.tgz or http://cvs.r-project.org/pub/CRAN/src/base/R-0.99.0.tgz or wait for it to be mirrored at a CRAN site near you within a day or two. There's also a version split in three (!) for floppies if you prefer that. The next release is to be 1.0.0 at the end of this month,
2000 Feb 07
2
R-0.99.0 is released
I've rolled up R-0.99.0.tgz a moment ago. You can get it from ftp://cvs.r-project.org/pub/CRAN/src/base/R-0.99.0.tgz or http://cvs.r-project.org/pub/CRAN/src/base/R-0.99.0.tgz or wait for it to be mirrored at a CRAN site near you within a day or two. There's also a version split in three (!) for floppies if you prefer that. The next release is to be 1.0.0 at the end of this month,
2012 Jan 29
0
Using influence plots and obtaining id numbers
I am a novice R user, and I am having difficulty understanding R's influence plots. I am trying to remove outliers from a particular variable, "sib." I am able to generate influence plots and further outlier information such as below (which is a shortened example). For my analyses, I end up excluding the points R refers to, 7, 18, 26, and 105. However, my question is, how can I
1999 Jun 23
1
Influence.measures
I am using rw0641 with Windows 98. To list just the influential repetitiones that result from "influence.measures", I am using the input result <- lm(y~x) and the code from the example in the help for "influence.measures" INFLM <- function(result){ inflm <- influence.measures(result) which(apply(inflm$is.inf,1,any)) } It works fine up to now with the
2013 Oct 18
2
pamer.fnc y la nueva versión de R
Javier, Creo que aquí aplica la ley de Linus que dice: "Dado un número suficientemente elevado de ojos, todos los errores se convierten en obvios". La persona que revisa y encuentra un error no necesariamente tiene que ser la misma que la que lo escribe. Una motivación muy importante al compartir un código es la de recibir los beneficios del control de calidad por parte de tus pares.