similar to: predict.lme / nlmmPQL: "non-conformable arguments"

> I'm trying to use "predict" with a linear mixed-effects logistic > regression model fitted with nlmmPQL from the MASS library. > Unfortunately, I'm getting an error "non-conformable arguments" in > predict.lme, and I would like to understand why. I'd like to briefly describe how I ended up working around this problem. The issue is that predict.lme

I've got a problem with "mcmcsamp" used with glmer objects produced with "lmer" from the lme4 package. When calling mcmcsamp, I get the error Error in if (var(y) == 0) { : missing value where TRUE/FALSE needed This does not occur with all models, but I can't find anything wrong with the dataset. If the error is in my data, can someone tell me what I am looking

>From posts in Sep 2004 and Feb 2005, glm() was raising "Error in x[good, ] * w : non-conformable arrays". I can reproduce this error using: df1 = data.frame(u=1:10, v=rpois(10,10), z=array(1,10,dimnames=list(1:10))) glm(v~u+offset(log(z)), data=df1, family=poisson) -- which seems to be due to the variable z have dimnames. In glm.fit(), the error is

Greetings R-helpers, I am attempting to fit an lme() while specifying a correlation structure, but I'm getting into trouble long before I get to that point. I am receiving the error: Error in y[revOrder] - Fitted : non-conformable arrays It doesn't seem to matter how simple or complex the model I specify is, it always gives this same error message. This makes me suspect something is

I am trying to calculate adjusted means according to a glm model with a Poisson distribution using effect() in the 'effects' package. I've done this many times before with great success, but this time I'm getting an error. My model contains two factors and two covariates/blocks and I would like the adjusted mean and confidence intervals for each factor separately. The model runs

Hi Everyone, I'm running some simulations where eventually I need to table the results. The problem is, that while most simulations I have at least one predicted outcome for each of the six possible categories, sometimes the algorithm assigns all the outcomes and one category is left out. Thus when I try to add the misclassification matrices I get an error. Is there a simple way I can make

Hello, Consider this function for generalized ridge regression: gre <- function (X,y,D){ n <- dim(X)[1] p <- dim(X)[2] intercept <- rep(1, n) X <- cbind(intercept, X) X2D <- crossprod(X,X)+ D Xy <- crossprod(X,y) bth <- qr.solve(X2D, Xy) } # suppose X is an (nxp) design matrix and y is an (nx1) response vector p <- dim(x)[2] D<- diag(rep(1.5,p)) bt

Hello, and thanks in advance! What does the error message "Error in x %*% coef(object) : non- conformable arguments" when indicate when predicting values for newdata with a model from bigglm (in package biglm), and how can I debug it? I am attempting to do Monte Carlo simulations, which may explain the somewhat interesting loop which follows. After the code I have included the output,

Hello all, I have generated a principal components regression model using the pcr() function from the PLS package (R version 2.12.0). I am getting a "non-conformable arguments" error when I try to use the predict() function on new data, but only when I try to read in the new data from a separate file. More specifically, when my data looks like this #########training data

With this patch, > A <- matrix(1, 2, 2) > B <- matrix(2, 3, 2) > A %*% B Error in A %*% B : non-conformable arguments of dimension (2, 2) and (3, 2) >From 205b591d4d14b5ff667325fb233a6deb08314726 Mon Sep 17 00:00:00 2001 From: Joshua Nathaniel Pritikin <jpritikin at pobox.com> Date: Fri, 5 Apr 2019 12:03:58 -0400 Subject: [PATCH] Improve non-conformable arguments error

I think this is a good idea. Is there a reason why it got no interest? Slippery slope? Or maybe others were also just occupied trying to figure out how Joshua's second message had timestamp earlier than his first message? On Fri, Apr 05, 2019 at 12:05:36PM -0400, Joshua N Pritikin wrote: >With this patch, > >> A <- matrix(1, 2, 2) >> B <- matrix(2, 3, 2) >> A

Hello, I am calculating this thing with vectors (b) and matrices (G,P): b'G/sqrt(b'Pb) where the denominator is a quadratic form and therefore always a scalar. In Scilab, it is quite simple: b'*G/sqrt(b'*P*b) However, in R, the denominator is an (1x1)matrix and R claims it is non conformable and I have to use drop() or as.numeric(). Like this: > b = 1:2 > G=diag(1,2) >

https://bugs.freedesktop.org/show_bug.cgi?id=92136 Bug ID: 92136 Summary: WebGL Conformance conformance/textures/texture-size-limit.html -> system freeze Product: Mesa Version: unspecified Hardware: Other OS: All Status: NEW Severity: normal Priority:

hi, does anzone know of a conformance testsuite e.g. for vorbis and theora bitstreams. This would be nice to have when e.g. testing a dsp based reimplementation. Also a testsuite that does robustness testing on the ogg container format would be nice. If none of these exist, wound't that be a good project for e.g. next GSoC? Stefan

This may not be regarded as a bug, but it actually affects and is sometimes boring. Suppose *foo* and *bar* are directories. When someone types: *rsync foo/ bar* rsync will sync foo/* into bar/ However, if he/she types: *mv foo/ bar* mv will move foo into bar/ and cp behaves like mv I think the trailing / shouldn't matter so much. What matters should be the asterisk after / This is

Hi, I am looking at the conformance test using opus_compare and the test vectors and I am a bit confused about FEC. Is there a way to validate that a decoder processes LBRR frames correctly? Thanks, Alexis

I hit a bug in libthr with pthread_mutexattr_settype which (at least as far as I understand the POSIX reference and also the man-page) makes it non-conformant to the specifications. Quoting: """ RETURN VALUES If successful, these functions return 0. Otherwise, an error number is returned to indicate the error. ... ERRORS ... The pthread_mutexattr_settype()

Prompted by todays wine news, I tried the winetest-latest.exe on my windows xp sp2 machine and received the following notification at the end of the test. --------------------------- Warning --------------------------- File too big (5.7 MB > 1.5 MB); submitting partial report. --------------------------- OK --------------------------- Is this normal?

I've run two conformance test binary (winetest-latest and winetest-8cbb8cc38d01) on Microsoft Windows Me 4.90.3000, both warned that Win9x was not supported, and I wouldn't be able to submit results. The lastest one said that there were about 67 tests failed (some wscript and msi error dialog appeared during the test) and it also said that there might be some problem with my

Dear community, I want to use conformal prediction to measure how good are my svm-regression predictions (having used library e1071). I have gone through the conformal package documentation. But I'm pretty newer and need some more and detailed examples. Can anybody help me? Thanks in advance, [[alternative HTML version deleted]]