similar to: interaction contrast

Hello, R experts, Sorry for asking this question again again since I really want a help! I have a two-factor experiment data and like to calculate estimates of interation contrasts say factor A has levels of a1, a2, and B has levels of b1, b2, b3, b4, and b5 with 3 replicates. I am not sure the constrast estimate I got is right using the script below:

Hello, R experts, I have a two-factor experiment data and like to calculate estimates of interation contrasts say factor A has levels of a1, a2, and B has levels of b1, b2, b3, b4, and b5 with 3 replicates. I am not sure the constrast estimate I got is right using the script below: score<-c(7.2,6.5,6.9,6.4,6.9,6.1,6.9,5.3,7.2,5.7,5.1,5.9,7.6,6.9,6.8,

Hello, R experts, Sorry for asking this question again since I really want a help! I have a two-factor experiment data and like to calculate estimates of interation contrasts say factor A has levels of a1, a2, and B has levels of b1, b2, b3, b4, and b5 with 3 replicates. I am not sure the constrast estimate I got is right using the script below:

Hello everyone, I am trying to estimate the parameter b. I have Y and X1 which I know and they are both random. However, I also have X2 which I don't know and is also random. I want to estimat b from the model: Y = b*X1 + ( 1 - b ) * X2 Can anyone offer some suggestions. The values of Y and X1 are both pvalues so they are constrained in (0,1). -- Thanks, Jim. [[alternative HTML version

Dear All, I am using a specific approach for my master thesis. In essence, a supervised reclassification is used as an intermediate step to find chemical parameters which are able to reclassify defined groups. These variables will be used in a next step where location and scale estimators of the groups are important. Traditionally linear discriminant analysis is used for reclassification which

Dear all, I'm using R 2.8.1 under Windows Vista on a dual core 2,4 GhZ with 4 GB of RAM. I'm trying to reproduce a result out of "Analysis of Financial Time Series" by Ruey Tsay. In R I'm using the fGarch library. After fitting a ar(3)-garch(1,1)-model > model<-garchFit(~arma(3,0)+garch(1,1), analyse) I'm saving the results via > result<-model

Dear everyone, I am doing some work about species richness estimation. Nonparametric estimation (such as Chao1, Jacknife1) can be done just using function "specpool()" and "estimateR()" in package "vegan". The problem is that I can not found any functions for parametric estimation (such as MMMeans, MMruns, Michaelis-Menten). Do you know any function for doing this?

Dear all, I have a question regarding the output of the coxph function. What does the 'max possible' exactly mean in the output below? Many thanks. coef exp(coef) se(coef) robust se z Pr(>|z|) smocc_zyban -0.4384 0.6451 0.8667 0.9473 -0.463 0.644 self 1.1857 3.2728 0.1405 0.1443 8.216 2.22e-16 *** smocc_zyban:self

Hi, I have a glm gives summary as follows, Estimate Std. Error z value Pr(>|z|) (Intercept) -2.03693352 1.449574526 -1.405194 0.159963578 A 0.01093048 0.006446256 1.695633 0.089955471 N 0.41060119 0.224860819 1.826024 0.067846690 S -0.20651005 0.067698863 -3.050421 0.002285206 then I use confint(k.glm)

I'm running a multinomial logit in R using the Zelig packages. According to str(trade962a), my dependent variable is a factor with three levels. When I run the multinomial logit I get an error message. However, when I run 'model=logit' it works fine. any ideas on whats wrong? ## MULTINOMIAL LOGIT anes96two <- zelig(trade962a ~ age962 + education962 + personal962 + economy962 +

Hello, and thank you in advance. I would like to capture the expected survival from a coxph model for subjects in an observational study with recurrent events, but the survexp statement is failing due to memory. I am using R version 2.13.1 (2011-07-08) on Windows XP. My objective is to plot the fitted survival with the Kaplan-Meier plot. Below is the code with output and [unfortunately]

Dear all, I hope to be the clearest I can. Let's say I have a dataset with 10 variables, where 4 of them represent for me a certain phenomenon that I call Y. The other 6 represent for me another phenomenon that I call X. Each one of those variables (10) contains 37 units. Those units are just the respondents of my analysis (a survey). Since all the questions are based on a Likert scale, they

por favor como se calculan las probabilidades para conformar el segundo vector SI.Distr, en este ejemplo puse la existente en SARS2003 #Análisis paso a paso rm(list = ls()) #existe información de la incidencia de casos de una enfermedad incidencia <-c (1,0,0,0,0,0,0,0,2,1,1,0,1,2,0,2,0,2,2,2,3, 1, 2, 0,2, 0, 1, 1, 2, 1, 1, 2, 3, 0, 1, 2, 0, 2, 1, 3, 1, 6, 3, 3,7, 4, 4, 3, 6,

I've posted this before but have not been able to locate what I'm doing wrong. I cannot determine how the forecast is made using the estimated coefficients from a simple AR(2) model when there is an exogenous variable. Does anyone know what the problem is? The help file for arima doesn't show the model with any exogenous variables. I haven't been able to locate any documents

R Help - I'm trying to run a correlation matrix with a covariate of "age" and will at some point will also want to covary other variables concurrently. I'm using the "psych" package and have tried other methods such as writing a loop to extract semi-partial correlations, but it does not seem to be working. How can I accomplish this? library(psych) > set.cor(y =

On Jul 24, 2011, at 3:02 AM, Duncan Sands wrote: > A big compile time regression. Any ideas? > > Ciao, Duncan. False alarm. For some reason that I have not yet been able to figure out, these tests run significantly more slowly when I run them during the daytime, which I did for that run. I checked a few of the worst regressions reported here and they all recovered in subsequent

A big compile time regression. Any ideas? Ciao, Duncan. On 22/07/11 19:13, llvm-testresults at cs.uiuc.edu wrote: > > bwilson__llvm-gcc_PROD__i386 nightly tester results > > URL http://llvm.org/perf/db_default/simple/nts/253/ > Nickname bwilson__llvm-gcc_PROD__i386:4 > Name curlew.apple.com > > Run ID Order Start Time End Time > Current 253 0 2011-07-22 16:22:04

Hi Stef and Alexey I have read some documents about CBQ algorithm from http://www.icir.org/floyd/cbq.html but still have some question about CBQ in Linux . 1. First estimator can estimate how much bandwidth already USED per class. one estimating algorithm is EWMA (exponential weighted moving average), how about Linux implemenatation about estimator? also do you have link for this algorithm? I

On Fri, Sep 14, 2007 at 11:42:18PM -0700, Tanya Lattner wrote: > The 2.1 pre-release (version 1) is available for testing: > http://llvm.org/prereleases/2.1/version1/ > > [...] > > 2) Download llvm-2.1, llvm-test-2.1, and the llvm-gcc4.0 source. > Compile everything. Run "make check" and the full llvm-test suite > (make TEST=nightly report). > > Send

Hi, I am analyzing a repeated-measures Greco-Latin Square with the aov command. I am using aov to calculate the MSs and then picking by hand the appropriate neumerator and denominator terms for the F tests. The data are the following: responseFinger mapping.code Subject.n index middle ring little ---------------------------------------------------------------------------- 1 1