similar to: simple multivariate linear model plot

Hello all, kind regards, I have imported a data.frame from SPSS using "foreign":read.spss but unfortunately it is reading dates in a way neither R nor myself can understand. > book$DATE [1] 13502246400 13443321600 13477795200 13472956800 13501728000 13445395200 13501382400 13502851200 13444185600 13461465600 13457232000 [12] 13458096000 13432435200 13431484800 13495334400

What is the recommended class for time of day (independent of calendar date)? And what is the recommended way to get the time of day from a POSIXct object? (Not a string representation, but a computable representation.) I have looked in the man page for DateTimeClasses, in the Time Series Analysis Task View and in Spector's Data Manipulation book but haven't found these. Clearly I can

Hi, I'm attempting to use the RODBC package on Windows Vista to import an excel spreadsheet. The spreadsheet has three worksheets the last of which is blank. Following an example in Phil Spector's book (p. 34), after creating a connection named con I did the following: > con RODBC Connection 3 Details: case=nochange DBQ=c:\temp\test.xls DefaultDir=c:\temp

Since we're on the topic of book reviews, I just received Phil Spector's new R book called "Data Manipulation with R" and it is also quite a nice book. I haven't gone through it all and I won't give a detailed review but I have gotten a lot out of the first 100 pages that I have read. Note that I've been using R for almost 1.5 years so , for me, it's a

I've read in Phil Spector's new book that it's a good idea to preallocate a big matrix, like u <- matrix(0,nrow,ncol) # (1) Now, I read contents of a huge matrix from a Fortran binary dump. u <- readBin(con,what="double",n=nrow*ncol) # (2) If I do (1) and then (2), u is a vector, obviously it's either reallocated or its matrix nature is lost -- overridden?

Is there an easy way to invert a table? (not to solve for the inverted matrix, just swap rows for columns & vice versa). I've gone through my data manipulation bible (Phil Spector's book), but to no avail. [[alternative HTML version deleted]]

Hello, I try to find a function for M-estimation in multivariate linear regression model (function that can estimate betas in my model: y=x * beta + e, where y is a matrix). I´ve searched R-site for a long time, but I am hopeless. I would like to ask, if there is any function for M-estimation in multivariate linear regression model in R. I know I can estimate betas in my model by rlm() function

I'm reading a old statistics book "MARVIN J. Karson (1982), Multivariate Statistical Methods, The IOWA State University Press, Iowa". In the chapter XI i can find some information about discrete multivariate analysis. This chapter is restricted to an introduction to log-linear models for analysis of multidimensional contingency tables. For example, in the log-linear model for

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

I'm following up on a question I posted 8/10/2010, but my newsreader has lost this thread. > Barrett & Ling, JASA, 1992, v.87(417), pp184-191 define general > classes of influence measures for multivariate > regression models, including analogs of Cook's D, Andrews & Pregibon > COVRATIO, etc. As in univariate > response models, these are based on leverage and

Hi! I would like to post the following question: I was trying to figure out how to do the simulation shown in Fig 10.6 of John Verzani's book 'Using R for Intro Statistics'. It is on page 290, with a description on the previous page. It seems like a simple thing... Just needing to duplicate a procedure. (Perhaps I need to do it with a loop?) This is what I was trying:

Barrett & Ling, JASA, 1992, v.87(417), pp184-191 define general classes of influence measures for multivariate regression models, including analogs of Cook's D, Andrews & Pregibon COVRATIO, etc. As in univariate response models, these are based on leverage and residuals based on omitting one (or more) observations at a time and refitting, although, in the univariate case, the

Dear R users, I am analyzing several response variables (all scaled to [0;1]) using a multivariate linear model. After fitting the model, I set up a hypothesis matrix to test specific contrasts for these response variables; for example: "a always increases significantly more than b when regressed against x". What I am stuck with now is how to calculate the correct F-values (and

Hi, I am working on a multivariate linear regression of the form y = Ax. I am seeing a great dispersion of y w.r.t x. For example, the correlations between y and x are very small, even after using some typical transformations like log, power. I tried with simple linear regression, robust regression and ace and avas package in R (or splus). I didn't see an improvement in the fit and

Dear all, i am doing linear regression with robust error to know the effect of a (x) variable on (y)other if i execute the command i found positive trend. But if i check the effect of number of (x.x1,x2,x3)variables on same (y)variable then the positive effect shwon by x variable turns to negative. so plz help me in this situation. Barjesh Kochar Research scholar

r-devel list, I have recently written an R package that solves a linear least squares problem, and computes the multivariate normal density function. The bulk of the code is written in C, with interfacing code to the BLAS and Lapack libraries. The motivation here is speed. I ran into a problem computing the determinant of a symmetric matrix in packed storage. Apparently, there are no explicit

I am trying to use dynamic loading of an outside C routine. I am attempting 6.12.1 of Phil Spector's book. When I try to load the object file I get an error I don't understand: > dyn.load("runa.o") Error in dyn.load(x) : unable to load shared library "/usr/home/tdlong/run_avg/runa.o": /usr/home/tdlong/run_avg/runa.o: ELF file's phentsize not the expected

I'm looking for a book for someone completely ignorant of statistics who wishes to learn both statistics and R. I've found three possibilities, one by Verzani ("Using R for Introductory Statistics"), one by Crawley ("Statistics: An Introduction using R"), and one by Dalgaard ("Introductory Statistics with R"). Do these books have different emphases,

I'm using Verzani's "Using R for Introductory Statistics" to teach a Research Methods in Psych course, and it recommends simple.median.test() for sign tests, which is in the Simple package--but nowhere I can find has ever heard of the Simple package! Anybody ever heard of this function or this package? cheers, Krysta ---------------------------- Krysta Chauncey, Ph.D.

I am trying to to write a wrapper function for the ode solver (under the package desolve) to enable it to take multivariate arrays. I know how to do it for 1 dimension arrays but my code breaks down when I try to do it for 2 dimensional arrays. Here is my code diffwrap<-function(t,y,mu)vdpol(t=t,A[1:3,1:4]<-y[1:12],B[1:12]<-y[13:24],mu=mu) vdpol<-function(t,A,B,mu) { list(c(mu,