similar to: Error in nonlinear mixed-effects model

Hello, Is there a simple way of stacking/merging two dataframes in R? I want to stack them piece-wise, not simply add one whole dataframe to the bottom of the other. I want to create as follows: x.frame: aX1 bX1 cX1 ... zX1 aX2 bX2 cX2 ... zX2 ... ... ... ... ... aX99 bX99 cX99 ... zX99 y.frame: aY1 bY1 cY1 ... zY1 aY2 bY2 cY2 ... zY2 ... ... ... ... ... aY99 bY99 cY99 ...

Hello I try to find probability values of some predictor combinations using logistic reg. in response level. Firstly I found coefficients by glm function. Then I followed two ways to get probability values: 1- probility <- exp(X0+bX1+cX2+...)/((1+exp(X0+bX1+cX2+...)) 2- probility <- predict(glm.obj,type="resp") Should have these two given same result ? if so, I did not have. Why

Hi there, Just wondering if anyone has any tips for using arrays? I am trying to convert the following SAS code to R: data A2; set A1; by subject_id; retain BX1-BX10 i; array b(1:10) BX1-BX10 ; if first.subject_id then do ; do j=1 to 10; b(j) = .; end; i=1; end; b(i) = BX; i = i+1; if last.subject_id then

Hi there, I have been trying to fit an NLME to my data. My dataset has two category levels - one is a fixed effect (level1) and one is a random effect (level2), though so far I have only experimented with the highest level grouping (fixed, level1), with the following code: mod1 <- nlme(H ~ a*(1-exp(-b*D^c)), data=sizes, fixed=a+b+c~factor(Loc), start=c(a=75,b=0.05,c=0.7)) This returns the

Hello I have a data set that looks like this; > b2 dato chr status PRRSvac PRRSsanVac PRRSsanDk PRRSdk 33 2007-12-03 090432 R?d SPF 34 2007-02-09 090432 R?d SPF+sanDK 35 2002-12-17 090432 R?d SPF+DK 36 2002-11-27 090432 R?d SPF+sanDK 37 2002-07-23

Dear all, I am trying to fit a nonlinear model with a autocorrelation term, but everytime I type in the command, I got an error message from Winwows and R closes itself. The command line is as follows: mod1<-nlme(V~A*exp(-B*A.O)*Vac.t.1.,data,fixed=A+B~1,random=A+B~1|ORDINAL,+ correlation=corCAR1(0.3179,~A.O|ORDINAL,TRUE),start=c(A=1.2,B=0.2)) I have already fitted this model allowing Phi to

Hello I have around 200 PDF-documents, containing data i want organized in R as a dataframe. The PDF-documents look like this; http://www.nabble.com/file/p21667074/PRRS-billede%2Bmed%2Bfarver.jpeg or like this; http://www.nabble.com/file/p21667074/PRRS-billede%2Bmed%2Bfarver%2B2.jpeg So i want to pull out the data in coloured boxes it become organized like this (just in R instead of

Dear R-users: I have some problems working with lme function, and i would be glad if anyone could help me. this kind of analysis i was used to do with PROC MIXED from SAS, but i would like to move to R, for many reasons... So, the problem is: Imagine the I have 3 factors: fact_A, fact_B and fact_C: The latter I would assume that is random, and the rest of them are fixed. Analysing the

Hi, (R version 2.15.0) I am running a pgm with 1 response (earlier standardized Y) and 44 independent vars (Xi) from the same data =a2: When I run the 'lm' function on single Xi at a time, the beta coefficient for let's say X1 is = -0.08 (se=0.03256) But when I run the same Y with 44 Xi-s with the 'step' function (because I left direction parameter empty, I assume a backward

Hello, I have a dataset concerning slugs. For each slug, the number of pumps per one time slot was counted. The number of pumps follows Bi(30, p) where p is very small, thus could be approximated by Poisson dist. (# of pumps is very often = 0) The slugs were observed during 12 time slots which are correlated in time as AR(1). The time slots are divided into two categories: Resting time

Estimados No tengo experiencia en programación y quisiera preparar el siguiente script para los estudiantes Una supuesta enfermedad, al parecer de transmisión aérea y que suele durar 7 días, entra en una localidad de 500 habitantes, la incidencia diaria es c(1,5,12,13,15,19,22,34,41,53,70) Al calcular Ro de la manera siguiente: library(R0) est.R0.AR(pop.size=500,

What fun. I don't often stoke up the boiler and actually compile open-source code, but here I am at the beginning of just such a joyous and wondrous adventure. I'm running the latest level of AIX (V5.3...V4.3 has been obsolete for at least, what, 5 years) and using the IBM compiler (xlc is similarly obsolete, from back when the compiler came with the O/S...oh, for the halcyon days of

Hola! I am encountering the following problem, in a multilevel analysis, using glmmPQL from MASS. This occurs with bothj rw1062 and r-devel, respectively with nlme versions 3.1-38 and 3.1-39 (windows XP). > S817.mod1 <- glmmPQL( S817 ~ MIEMBROScat+S901+S902A+S923+URBRUR+REGION+ + S102+S103+S106A+S108+S110A+S109A+S202+S401+S557A+S557B+ + YHOGFcat,

Dear all: Y=a+bX1+cX2 In the Gee (Generalized Estimation Equation) arguments: The arument Corstr has sveral choices: "independence" "fixed" "stat_M_dep" "non_stat_M_dep" "exchangeable" "AR-M" "unstructured" What does each term mean? How do I choose among them? How do I know the correlation structure of

I have a program which is doing a few thousand runs of lm(). Suppose it is a simple model y = a + bx1 + cx2 + e I have the R object "d" where d <- summary(lm(y ~ x1 + x2)) I would like to obtain Var(x2) out of "d". How might I do it? I can, of course, always do sd(x2). But it would be much more convenient if I could snoop around the contents of summary.lm and

Hello list, why is it that GoToIfTime thinks a date of **|*|29-*|jun *is not valid ?? [Jun 29 14:06:34] -- Executing [s at macro-vac:10] *GotoIfTime*("SIP/testcorp-00000036", "**|*|29-*|jun*?onvac") in new stack [Jun 29 14:06:34] WARNING[3076]: pbx.c:4127 get_range: Invalid end day '*', assuming none [Jun 29 14:06:34] -- Executing [s at macro-vac:11]

Using IBM's C for AIX V9 with Ralf Becker's AIX adaption, I see this: + exec /usr/vac/bin/xlc -DHAVE_CONFIG_H -I. -I. -I../.. -I/opt/freeware/include/ openssl -g -c close-keep-errno.c -M source='compat.c' object='compat.o' libtool=no DEPDIR=.deps depmode=aix /bin/sh ../../depcomp /usr/local/dovecot/dovecot-cc -DHAVE_CONFIG_H -I. -I. -I ../..

Adam: Thanks for putting up this page. But something is wrong. In particular, our Powerware 9135 is a three phase UPS system with THREE 480 volt outputs. So the displayed voltage is not correct -- in fact there should really be THREE voltages displayed, all around 480v. Nut developers: I am copying the NUT mailing list to see if anyone can suggest how to fix this. NUT developers, see the

Hei Group, I want to compare the relative importance of predictors in a multiple linear regression y~a+bx1+cx2... However, bptest indicates heteroskedasticity of my model. I therefore perform a robust regression (rlm), in combination with bootstrapping (as outlined in J. Fox, Bootstrapping Regression Models). Now I want to compare the relative importance of my predictors. Can I rely on the

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