similar to: mspath analyzes transitions between multiple state with history dependence

I have code and documentation that don't match, but R CMD check didn't flag it. in mspath.R mspath <- function(formula, # formula with observed Markov states ~ observation times (required) qmatrix, # matrix of 1s and 0s with indices of allowed transitions (diagonal is ignored) (required) misc = FALSE, ematrix = NULL, # matrix

Hello I want to build a classification tree for a binary response variable while the condition for the final tree should be : The total misclassification for each group (zero or one) will be less then 10% . for example: if I have in the root 100 observations, 90 from group 0 and 10 from group 1, I want that in the final tree a maximum of 9 and 1 observations out of group 0 and 1, respectively,

Greetings R world, I know some version of the this question has been asked before, but i need to save the output of a loop into a data frame to eventually be written to a postgres data base with dbWriteTable. Some background. I have developed classifications models to help identify problem accounts. The logic is this, if the model classifies the record as including variable X and it turns out

I get the error undefined symbol: Rf_rownamesgets when I try to load my package, which include C++ code that calls that function. This is particularly strange since the code also calls Rf_classgets, and it loaded OK with just that. Can anyone tell me what's going on? For the record, I worked around this with the general purpose attribute setting commands and R_RowNamesSymbol. I

The cran2deb archives target testing. I just pulled a package from them onto a stable system; the library loaded but said > library(akima) Warning message: package 'akima' was built under R version 2.10.0 Are this and other packages likely to work correctly with different R's (2.7 in the case of stable)? How well are they likely to work with a backported R? The R version would

At the moment I've no host with which to test ppp/lp things on. If you (or anyone) could provide complete regexes, (each beginning with ^ and ending with $) I will patch the rules accordingly. If not, sending the full log lines is a good start. Thanks! -- [ Todd J. Troxell ,''`. Student, Debian GNU/Linux Developer, SysAdmin, Geek :

Greetings, I'm using MSM (mutli-state markov modeling) package to study the progression of fibrosis in U.S hepatitis C population. I find this is a very fascinating tool for an applied researcher like myself. I have a four stage progression only model without any absorbing stage, also assuming no misclassification error in the data for the time being. I also have a couple covariates in the

I'm having trouble getting correct help output in some circumstances for a package I've created. Though this is not an issue with the current R, I would like my package to work with previous ones as well. I'm looking for suggestions about how I could rework my .Rd file so that it will work with prior R's. In particular, R 2.7 is in the latest stable release of Debian, so I'd

I can't tell from the docs ("Writing R Extensions" 1.9.1) exactly what environment the tests, examples, and vignettes that R CMD check tries to run are in. In particular: 1) how do I get the package loaded? 2) how do I access data in the data/ directory? 3) where is the material in the other directories? (e.g., has inst/ material been installed? where?) Apparently (section 1.3)

Dear friends, I'm examining the characteristics of two models that both fit the sodium concentration in 16 pigs quite well under treatment or control conditions. The more complicated model is by anova better than the less complicated model. To take it further I have generated replicate data using the independent variables and parameter estimates under the two models. A clinically

I've attached a script I wrote that pulls all the setGeneric definitions out of a set of R files and puts them in a separate file, default allGenerics.R. I thought it might help others who find themselves in a similar situation. The "situation" was that I had to change the order in which files in my package were parsed; the scheme in which the generic definition is in the

Hi all, I am working for nest box occupancy data for birds and would like to construct a Markov transition matrix, to derive transition probabilities for ALL years of the study (not separate sets of transition probabilities for each time step). The actual dataset I'm working with is 125 boxes over 14 years that can be occupied by 7 different species, though I have provided a slimmed down

Dear experts, I have to generate 1000 transitions of a discrete time Markov Chain and then give and estimation of the equilibrium distribution. I know the transition matrix. 0.3 0.7 0 0.2 0.5 0.3 0 0.4 0.6 Do you know how to do it with R? Thanks a lot! Estefania [[alternative HTML version deleted]]

Hi users I'm student who is struggling with basic R programming. Would you please help me with this problem. "My english is bad" I hope that my question is clear: I have a matrix in wich there are two colmns( yp, yt) Yp: predicted values from my model. yt: true values ( my dependante variable y is a categorical;3 modalities (0,1,2) I don't know how to procede to calculate the

Package: logcheck-database Version: 1.2.63 Severity: normal Tags: patch spamassassin is now reporting Unix domain sockets in the rport field. I'm not exactly sure what changed to cause this to happen; it started after an upgrade whose only remotely relevant package was razor. I think the following pattern in ignore.d.server/spamd will work ^\w{3} [ :0-9]{11} [._[:alnum:]-]+

HI Is there any function in R that tells us error rate(misclassification rate) for logistic regression type classification? i also want to know the function to determine type I and type II error. I have found a link where "misclass" and "confusion" are used. But I dont know the package name. http://alumni.media.mit.edu/~tpminka/courses/36-350.2001/lectures/day32/

Hi all, Can anyone who is familar with CART tell me what I missed in my tree code? library (MASS) myfit <- tree (y ~ x1 + x2 + x3 + x4 ) # tree.screens () # useless plot(myfit); text (myfit, all= TRUE, cex=0.5, pretty=0) # tile.tree (myfit, fgl$type) # useless # close.screen (all= TRUE) # useless My current tree plot resulted from above code shows as:

Hello, I am pretty new to R, I have always used SAS and SAS products. My target variable is binary ('Y' and 'N') and i have about 14 predictor variables. My goal is to compare different variable selection methods like Forward, Backward, All possible subsests. I am using misclassification rate to pick the winner method. This is what i have as of now, Reg <- glm (Graduation ~.,

Hi, I think I'm missing something very obvious, but I am missing it, so I would be very grateful for help. I'm using rpart to analyse data on skull base morphology, essentially predicting sex from one or several skull base measurements. The sex of the people whose skulls are being studied is known, and lives as a factor (M,F) in the data. I want to get back predictions of gender, and

Hi everybody, I am new in e1071 and with SVMs. I am trying to understand the performance of SVMs but I face with a situation that I thought as not meaningful. I added the R code for you to see what I have done. /set.seed(1234) data <- data.frame( rbind(matrix(rnorm(1500, mean = 10, sd = 5),ncol = 10), matrix(rnorm(1500, mean = 5, sd = 5),ncol = 10))) class <- as.factor(rep(1:2,