similar to: Multivariate multiple regression

Dear All, I would be very appreciative of your help with the following 1). I am running multivariate multiple regression through the manova() function (kindly suggested by Professor Venables) and getting two different answers for test=c("Wilks","Roy","Pillai") and tests=c("Wilks","Roy",'"Pillai") as shown below. In the

Hello, I would like to perform a multivariate regression analysis to model the relationship between m responses Y1, ... Ym and a single set of predictor variables X1, ..., Xr. Each response is assumed to follow its own regression model, and the error terms in each model can be correlated. Based on my readings of the R help archives and R documentation, the function lm() should be able to

I'd like to sample multiple response values from a multivariate regression fit. For example, suppose I have m=2 responses (y1,y2) and a single set of predictor variables (z1,z2). Each response is assumed to follow its own regression model, and the error terms in each model can be correlated (as in example 7.10 of section 7.7 of Johnson/Wichern): > ex7.10 <- + data.frame(y1 =

Hi Everyone, I have some data that predicts both a nominal and ordinal response variable. I was wondering what packages in R would help me analyze the data? I was also curious if anyone could recomend me some textbooks that would help with the analysis of such data? I have the 5th edition of "Applied Multivariate Statistical Analysis" by Richard A. Johnson and Dean W. Wichern

I'm trying to write some functions extending influence measures to multivariate linear models and also allow subsets of size m>=1 to be considered for deletion diagnostics. I'd like these to work roughly parallel to those functions for the univariate lm where only single case deletion (m=1) diagnostics are considered. Corresponding to stats::hatvalues.lm, the S3 method for class

I''ve been searching for ages and not come up with anything on the internet. I was wondering if there is a Rails equiv. for the PHP function str_replace. For example; variable_for_new_string("value_to_repace", "string_to_replace_with", "string_to_perform_modification_to") Thanks in advance for any help. -- Posted via http://www.ruby-forum.com/.

It seems that confint.default returns an empty data.frame for objects of class mlm. For example: ``` nobs <- 20 set.seed(1234) # some fake data datf <- data.frame(x1=rnorm(nobs),x2=runif(nobs),y1=rnorm(nobs),y2=rnorm(nobs)) fitm <- lm(cbind(y1,y2) ~ x1 + x2,data=datf) confint(fitm) # returns: 2.5 % 97.5 % ``` I have seen proposed workarounds on stackoverflow and elsewhere, but

Hello, suppose I have a multivariate multiple regression model such as the following: > DF<-data.frame(x1=rep(c(0,1),each=50),x2=rep(c(0,1),50)) > tmp<-rnorm(100) > DF$y1<-tmp+DF$x1*.5+DF$x2*.3+rnorm(100,0,.5) > DF$y2<-tmp+DF$x1*.5+DF$x2*.7+rnorm(100,0,.5) > x.mlm<-lm(cbind(y1,y2)~x1+x2,data=DF) > coef(x.mlm) y1 y2 (Intercept)

I have created a ''admin'' controller and all the necessary definitions and templates to delete, update and edit records and this is working OK, but how do I effectively restrict access to these defs'' from all but the admin user (called admin)? Currently I am just using if statements within the defs'' to check if it is the admin user logged in e.g; def index

Hi all, I am experimenting the function "manova" in R. I tried it on a few data sets, but I did not understand the result: I used "summary(manova_result)" and "summary(manova_result, test='Wilks')" and they gave a bunch of numbers... But I need the Sum-of-Squares of BETWEEN and WITHIN matrices... How do I read off from the R's manova results? Any

When I fit a multivariate linear model, and the formula is defined outside the call to lm(), the method summary.mlm() fails. This works well: > y <- matrix(rnorm(20),nrow=10) > x <- matrix(rnorm(10)) > mod1 <- lm(y~x) > summary(mod1) ... But this does not: > f <- y~x > mod2 <- lm(f) > summary(mod2) Error en object$call$formula[[2L]] <- object$terms[[2L]]

I would like to perform multiple comparisons or post-hoc testing on the independent variable in an Anova.mlm object generated by the Anova function of the car package. I have defined a multivariate linear model and subsequently performed a repeated measures ANOVA as per the instructions in section #3 of the following comprehensive tutorial on the subject from the Gribble lab at UWO:

Dear list, I have been using multivariate multiple regression (MMR) in the form lm(Y~X) where Y and X are matrices of response and predictor variables. I know that summary(mlm.object) would give the usual lm statistics for each response variable separately and that anova.mlm(mlm.object) will give the analysis of variance table of the mlm object. However, anova.mlm (also manova(mlm.object))

Dear R fans, I have got a difficult sounding problem. For fitting a linear model using continuous response and then for re-fitting the model after excluding every single variable, the following functions can be used. library(MASS) model = lm(perf ~ syct + mmin + mmax + cach + chmin + chmax, data = cpus) dropterm(model, test = "F") But I am not sure whether any similar functions is

Hello, I've just fitted a model with multi-responses, and I get an object of class "lm" "mlm". My problem is that as soon as I invoke the predict method for a dataframe "newdata", the methods runs and give me back prediction at the fitting points but not for newdata. Does someone has an explanation for this behavior, and some ideas to make predict.mlm work

Hi, Am newish to stats and R, so I certainly appreciate any help. Basically I have 50 inidividuals whom I have 6 photos each of their optic nerve head. I want to check that the orientation of the nerve head is consistent, ie the 6 replicates show minimal or preferably no rotation differences. I'll draw an arbitrary line between some blood vessels (same reference in each set of replicates) and

I'm trying to write a function to find the means over factors of the responses in a mlm (something I would do easily in SAS with PROC SUMMARY). The not-working stub of a function to do what I want is below, and my problem is that I don't know how to call aggregate (or some other function) in the context of terms in a linear model extracted from a lm/mlm object. means.mlm <-

Hi everybody I am trying to run the next code but I have the next problem Y1<-cbind(score.sol, score.com.ext, score.pur) > vol.lm<-lm(Y1~1, data=vol14.df) > library(MASS) > stepAIC(vol.lm,~fsex+fjob+fage+fstudies,data=vol14.df) Start: AIC=504.83 Y1 ~ 1 Error in addterm.mlm(fit, scope$add, scale = scale, trace = max(0, trace - : no addterm method implemented for

Dear helpeRs, the following data set comes from Johnson/Wichern: Applied Multivariate Statistical Analysis, 6th ed, pp. 304-306. /X <- structure(c(9, 6, 9, 3, 2, 7), .Dim = as.integer(c(3, 2))) Y <- structure(c(0, 2, 4, 0), .Dim = as.integer(c(2, 2))) Z <- structure(c(3, 1, 2, 8, 9, 7), .Dim = as.integer(c(3, 2)))/ I would like to compute Wilk's Lambda in R, which I know is 0.0385.

Dear list, I use Sweave almost exclusively for writing papers, and I have become quite spoiled by the excellent xtable export facilities. Has anybody written an xtable method for the Anova function in CAR, or has anybody used a different set of functions to import Anova results into a table in an Sweave document? If not, any handy hints on how to write a good homebrew based on the output of Anova