similar to: subscripts for panel.superpose in lattice

Dear R-helpers, I would appreicate if someone can help me on the transfer parameter in ARIMAX and also see what I am doing is correct. I am using ARIMAX with 2 Exogeneous Variables and 10 years data are as follows: DepVar Period, depVar, IndepVar1 Period, indepVar1, IndepVar2 Period, indepVar2 Jan 1998,708,Jan 1998,495,Jan 1998,245.490 Feb 1998,670,Feb 1998,421.25,Feb 1998,288.170 Mar

I am trying to specify a mixed model for my research, but I can't quite get it to work. I've spent several weeks looking thru various online sources to no avail. I can't find an example of someone trying to do precisely what I'm trying to do. I'm hoping some smart member of this mailing list may be able to help. First off, full disclosure: (1) I'm an engineer by trade, so

Hi! I need to run ols regressions with Huber-White sandwich estimators and the correponding standard errors, without an intercept. What I'm trying to do is create an ols object and then use the robcov() function, on the order of: f <- ols(depvar ~ ind1 + ind2, x=TRUE) robcov(f) However, when I go f <- ols(depvar ~ ind1 + ind2 -1, x=TRUE) I get the following error: Error in

Greetings R-help! I'm fairly new to R and am trying to expand my knowledge beyond using R for simple summary statistics and basic tests. To that end I am attempting to write an interactive R-script that will perform a general rational function fit to a given dataset based on the example given at http://www.itl.nist.gov/div898/handbook/pmd/section6/pmd64.htm. The problem that I seem to have

Hi all, I have been working through the examples in one of the vignettes associated with the 'mlogit' package, 'Kenneth Train's exercises using the mlogit package for R.' In spite of using the code unchanged, as well as the data used in the examples, I have been unable to run a Wald test to test two models. Specifically, I have run the following command, where mc and mi2 are

Hi I'm performing a PLS This is my data present in a file Year Y X2 X3 X4 X5 X6 1960 27.8 397.5 42.2 50.7 78.3 65.8 1960 29.9 413.3 38.1 52 79.2 66.9 1961 29.8 439.2 40.3 54 79.2 67.8 1961 30.8 459.7 39.5 55.3 79.2 69.6 1962 31.2 492.9 37.3 54.7 77.4 68.7 My R-code Data <- read.csv("C:/TestData.csv") variable=names(Data)[4:8] dataset=NULL dataset$X=NULL len=length(variable)

I need to play games with an expression similar to the following one: print(xyplot(DepVar ~ Group|Covar, groups=Othergroup, data=mydf, pch = 18 ,main="Testcase",auto.key = TRUE)) The problem is that the formula argument (the first argument) an the groups argument are passed over from another program as strings. The formula argument does not pose problems, I can do

Hello I have been struggling with this simple looking problem. I have two dataframes. The first one contains ID, date, and revenue information for specific suppliers. id lastdate depvar A 5/10/2017 10 B 8/16/2017 20 C 2/14/2017 30 D 9/5/2017 40 E 8/1/2017 50 F 11/4/2017 60 G 6/22/2017 70 The second dataframe contains timeseries data of each supplier in different columns. For example Column A are

Hi, I was wondering if you could help me: The following are the first few lines of my data set: subject group condition depvar s1 c ver 114.87 s1 c feet 114.87 s1 c body 114.87 s2 c ver 73.54 s2 c feet 64.32 s2 c body 61.39 s3 a ver 114.87 s3 a feet 97.21 s3 a body 103.31 etc. I entered the following ANOVA command: >dat <- read.table("mydata.txt", header=T)

Dear R listers, I am learning the MLE utility optim() in R to program ordered logit models just as an exercise. See below I have three independent variables, x1, x2, and x3. Y is coded as ordinal from 1 to 4. Y is not yet a factor variable here. The ordered logit model satisfies the parallel regression assumption. The following codes can run through, but results were totally different from what I

A multinomial logit model can be specified as a conditional logit model after restructuring the data. Doing so gives flexibility in imposing restrictions on the dependent variable. One application is to specify a loglinear model for square tables, e.g. quasi-symmetry or quasi-independence, as a multinomial logit model with covariates. Further details on this technique and examples with several

Hi, Can someone tell me if it is possible to set the dispersion parameter constant when fitting a negative binomial glm in R? I've looked at the documentation and can't find the appropriate argument to pass. In STATA I can type: nbreg depvar [indepvar...], offset(offset) dispersion(constant). Thank you [[alternative HTML version deleted]]

Hello R-help, According to a research article that covers the topic I'm analyzing, in Stata, a Poisson pseudo-maximum-likelihood (PPML) estimation can be obtained with the command poisson depvar_ij ln(indepvar1_ij) ln(indepvar2_ij) ... ln(indepvarN_ij), robust I looked up Stata help for the command, to understand syntax and such: www.stata.com/help.cgi?poisson Which simply says

HELLO ALL, I AM GETTING AN ERROR MESSAGE WHEN TRYING TO RUN A GAMM MODEL LIKE THE ONE BELOW. I AM USING R VERSION 2.14.1 (2011-12-22) AND MGCV 1.7-12. M1 <-gamm(DepVar ~ Treatment + s(Year, by =Treatment), random=list(Block=~1), na.action=na.omit, data = mydata, correlation = corARMA(form =~ Year|Treatment, p = 1, q = 0)) THIS IS THE ERROR MESSAGE Error in `*tmp*`[[k]] : attempt to

Just wanted to alert everyone regarding a problem that I only experience with R2.9.0 and not with R2.8.1 when I run both using exactly the same script and the same data. Here is what I do with my data "MyData", 2 predictors (V1 and V2) and my survival DV "Depvar": library(survival)

Sorry for posting a possibly stupid question. I am using aov() for calculating ANOVA as follows: summary(aov(depVar~factor1*factor2+Error(subject/(factor1+factor2)), data=anovaAllData)) and usually all works fine. How exactly the call has to look if I want to use lm() directly to obtain the same results. The problem is that due to several reasons I am missing single data points such that I

Edward, you also can use the package aod on CRAN, see the help page of the function negbin. Best Matthieu An example: > library(aod) > data(dja) > negbin(y ~ group + offset(log(trisk)), ~group, dja, fixpar = list(4, 0)) Negative-binomial model ----------------------- negbin(formula = y ~ group + offset(log(trisk)), random = ~group, data = dja, fixpar = list(4, 0))

We occasionally utilize the coxph function in the survival library to fit multinomial logit models. (The breslow method produces the same likelihood function as the multinomial logit). We then utilize the predict function to create summary results for various combinations of covariates. For example:

Hi everybody, using bwplot for producing panel boxplot with 3 dimensions i want to add a mark on each boxplot representing one individual (on all its dimensions) till now, i didn't succeed getting the desired solution I want as well to keep the median symbols as a line Many thanks for your help christophe here is the tested code: ######################## library(lattice) ex <-

Hello, ? I am struggling with a lattice graph. I want to plot points and condition on a variable called 'Method'. For each conditional plot I have two subgroups, say: 'first'and 'second'. I want to plot the points in a conditional graph with a different color or symbol for each subgroup. ? Moreover I want to calculate within each conditional graph limits of the points