search for: mlm

..."lm" objects, > hatvalues <-function (model, ...) UseMethod("hatvalues") > hatvalues.lm <- function (model, infl = lm.influence(model, do.coef = FALSE), ...) { hat <- infl$hat names(hat) <- names(infl$wt.res) hat } I have, for class "mlm" objects hatvalues.mlm <- function(model, m=1, infl=mlm.influence(model, m=m, do.coef = FALSE), ...) { hat <- infl$H m <- infl$m names(hat) <- if(m==1) infl$subsets else apply(infl$subsets,1, paste, collapse=',') hat } where mlm.influence() does the...

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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: http://gribblelab.org...

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 e...

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) 0.07800993 0.2303557 x1 0.52936947 0.3728513 x2 0.13853332 0.4604842 How can I test whether x1 and x2 respectively have the same effect on y1 and y2? In other words, how can I test...

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: 1) The univari...

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]] <- as.name(yna...

...ect to change as loose ideas get confronted by the harsh realities of programming. Comments are welcome. They might even influence the implementation... -pd General considerations: - S3 class based to fit existing code - similar to lm/glm code fit <- lm(Y~...) creates basic mlm object (already does) SSD(obj) returns object of class "SSD": $SSD matrix of sums of squares & products $df degrees of freedom. Methods for (lm and) mlm. estVar(obj) obj$SSD/obj$df (could have methods for lm/mlm too) Convenience functions: Tr...

>>>>> steven pav >>>>> on Thu, 19 Jul 2018 21:51:07 -0700 writes: > It seems that confint.default returns an empty data.frame > for objects of class mlm. For example: > It seems that confint.default returns an empty data.frame for objects of > class mlm. Not quite: Note that 'mlm' objects are also 'lm' objects, and so it is confint.lm() which is called here and fails. > For example: > > ``` > nobs <- 20 >...

Full_Name: Yves Rosseel Version: 2.2.1 OS: Submission from: (NULL) (157.193.116.152) The code below sketches a possible implementation of a function 'mlh.mlm' which I think would be a good complement to the 'anova.mlm' function in the stats package. It tests a single linear hypothesis of the form H_0: LBT'= 0 where B is the matrix of regression coefficients; L is a matrix with rows giving linear combinations of the regressions coefficien...

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 efficiently. Tha...

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)) presents the significances of each predictor variable as an anova table, but I wan...

Full_Name: Yves Rosseel Version: 2.2.1 OS: i686-pc-linux-gnu Submission from: (NULL) (157.193.116.152) Dear developers, For the single-model case, the anova.mlm() function does not seem to handle multi-parameter predictors (eg factors) correctly. A toy example illustrates the problem: Y <- cbind(rnorm(100),rnorm(100),rnorm(100)) A <- factor(rep(c(1,2,3,4), each=25)) fit <- lm(Y ~ A) anova.mlm(fit) gives Error in T %*% ss[[i]] : non-conformable...

...2 1 x 2 2 x 2 3 x 2 4 x 2 5 x 2 6 x etc I'm wanting to test for Sphericity (because I've read that you should - is this routine in a repeated measures ANOVA?) and can see that Anova.mlm in the CAR package offers this in addition to the alternative Greenhouse and Feldt tests. I just don't really know how to perform the test - can someone give me some help. Thank you. Paul Dept of Ophthalmology Uni Melbourne, Australia -- View this message in context: http://www.nabble.com/...

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

...p="_"), c("A", "B", "C", "D", "E"))) There are 140 features describing 5 different plant species. I want to retain only those features that show good performance in model (by using a function similar to dropterm, which can not be used for mlm objects). I wud appreciate some hints n suggestions. Thx - Vickie [[alternative HTML version deleted]]

...ted > ex7.10 <- + data.frame(y1 = c(141.5, 168.9, 154.8, 146.5, 172.8, 160.1, 108.5), + y2 = c(301.8, 396.1, 328.2, 307.4, 362.4, 369.5, 229.1), + z1 = c(123.5, 146.1, 133.9, 128.5, 151.5, 136.2, 92), + z2 = c(2.108, 9.213, 1.905, .815, 1.061, 8.603, 1.125)) > attach(ex7.10) > f.mlm <- lm(cbind(y1,y2)~z1+z2) > y.hat <- c(1, 130, 7.5) %*% coef(f.mlm) > round(y.hat, 2) y1 y2 [1,] 151.84 349.63 > qf.z <- t(c(1, 130, 7.5)) %*% + solve(t(cbind(1,z1,z2)) %*% cbind(1,z1,z2)) %*% + c(1, 130, 7.5) > round(qf.z, 5) [,1] [1,] 0.36995 >...

I'm looking for something in R to fit a multivariate linear model robustly, using an M-estimator or any of the myriad of other robust methods for linear models implemented in robustbase or methods based on MCD or MVE covariance estimation (package rrcov). E.g., one can fit an mlm for the iris data as: iris.mod <- lm(cbind(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width) ~ Species, data=iris) What I'd like is something like rlm() in MASS, but handling an mlm, e.g., iris.mod <- rmlm(cbind(Sepal.Length, Sepal.Width, Petal.Length, Petal.Width) ~ Species, data=...

I believe there is a coding error in the first part of predict.mlm in the splines package, but perhaps someone could explain the logic to me if I'm wrong. I don't see how the second if (missing(newdata)) could ever be true. (I would show the code but I'm using email on a different machine than R today.) Paul Gilbert -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-...

...10-02-12) o Added demo/Big5.R o fixed buglet with text3d causing rgl to crash (thx: Duncan Murdoch) o switched inst/CHANGES to NEWS o Added data/RatWeight and examples o Added data/Headache and examples o Fixed buglets in heplot, heplot1d, heplot3d regarding number of variables o Added etasq.mlm methods for multivariate measures of association (\eta^2) o Return ellipse radius from heplot, heplot3d Version 0.9-1 (2010-01-1) o heplot.mlm, pairs.mlm, heplot3d.mlm now work for repeated measure designs with only covariates on the rhs. o Implemented heplot1d() for repeated measures design...