similar to: linear probability model

Hi, I want to fit 3 beta distributions to my data which ranges between 0 and 1. What are the functions that I can easily call and specify that 3 beta distributions should be fitted? I have already looked at normalmixEM and fitdistr but they dont seem to be applicable (normalmixEM is only for fitting normal dist and fitdistr will only fit 1 distribution, not 3). Is that right? Also, my data has 26

Hello, dear experts. I don't have much experience in building regression models, so sorry if this is too simple and not very interesting question. Currently I'm working on the model that have to predict proportion of the debt returned by the debtor in some period of time. So the dependent variable can be any number between 0 and 1 with very high probability of 0 (if there are no payment)

Hello! When I am analyzing proportion data, I usually apply logistic regression using a glm model with binomial family. For example: m <- glm( cbind("not realized", "realized") ~ v1 + v2 , family="binomial") However, sometimes I don't have the number of cases (realized, not realized), but only the proportion and thus cannot compute the binomial model. I just

Dear list, I am trying to replicate an econometrics study that was orginally done in Stata. (Blanton and Blanton. 2009. A Sectoral Analysis of Human Rights and FDI: Does Industry Type Matter? International Studies Quarterley 53 (2):469 - 493.) The model I try to replicate is in Stata given as xtpcse total_FDI lag_total ciri human_cap worker_rts polity_4 market income econ_growth log_trade

Hello, I am trying to use the plm package for panel econometrics. I am just trying to get started and load my data. It seems from most of the sample documentation that I need to use the pdata.frame function to get my data loaded. However, even after installing the "plm" package, my R installation cannot find the function. I am trying to follow the example in plmEN.pdf (

Dear useRs, version 2.2-2 of the "betareg" package has just been released on CRAN http://CRAN.R-project.org/package=betareg accompanied by an article in the Journal of Statistical Software http://www.jstatsoft.org/v34/i02/ The package provides beta regression for data in the unit interval (0, 1) such as rates and proportions. The manuscript replicates several practical

Dear useRs, version 2.2-2 of the "betareg" package has just been released on CRAN http://CRAN.R-project.org/package=betareg accompanied by an article in the Journal of Statistical Software http://www.jstatsoft.org/v34/i02/ The package provides beta regression for data in the unit interval (0, 1) such as rates and proportions. The manuscript replicates several practical

Hello list, I'm following the paper (http://www.jstatsoft.org/v27/i02/paper) on how to use "plm" to run panel regressions, and am having trouble with what I believe should be something very basic. When I run the command (p.9 in the paper): R> dynformula(emp~wage+capital,log=list(capital=FALSE,TRUE),lag=list(emp=2,c(2,3)),diff=list(FALSE,capital=TRUE)) I see: emp ~ wage +

I am working with panel data. I am using the plm package to do this. I would like to do be able to adjust for autocorrelation, as one does with glm models and correlation structures (eg corr=corARMA(q=4)) . In particular, I want to employ MA(4) error structure. Is there a way of doing this with the plm package? (Note: I do not really want to use the pggls function for various

Hi all, I am using package lavaan and have created a structural equation model with two exogenous and seven endogenous variables with the following relationships #specify the model m1 = ' # regressions D ~ ma + hs + b4 + b5 + b15 + b16 ma ~ hs + b4 + b5 + b15 + b16 hs ~ b4 + b5 + b15 + b16 b4 ~ el + la b5 ~ el + la

Hi, I have experimental response (Y) and many (important or not) actions (X). I want to create model: Y = aX1 + bX2 + ... + eX5 (1) from few most important actions of course. As I understand I have to use plsr for this task. I learned read.table and plsr R functions and how to plot some results from them, but still do not understand how I can get (or construct) function I need (function 1)?

Dear R List, I have found that R handles a remarkable number of analytic tasks that are overlooked by major commercial packages. However, I have not found an R package that handles MaxDiff Scaling - does one exist? Thanks in Advance, Stephen Brand

Dear r-helpers, I am working with plm package. I am trying to fit a fixed effects (or a 'within') model of the form y_it = a_i + b_i*t + e_it, i.e. a model with an individual-specific intercept and an individual- specific slope. Does plm support this directly? Thanks in advance! Otto Kassi

Hi, With some help I learned how to use plsr(Y~x, 2, data=my) function in R (and build "my" from vector "Y" and matrix "x"). But still I have question about results interpretation. In the end I want to construct prediction function in form: Y=a1x1+a2x2 But I do not understand how to do it. Documentation do not describe this. Thanks for help. ;) [[alternative HTML

hi R help group, I have installed PLS package in R and use it for princomp & prcomp commands for calculating PCA using its example file(USArrests example). But How I can use PLS for Partial least square, R square, mvrCv one more think how i can import external file in R. When I use plsr, R2, RMSEP it show error could not find function plsr, RMSEP etc. How I can calculate PLS, R2, RMSEP, PCR,

Hi all, I a semi-beginner with R and I am working with the plm package to examine a longitudinal dataset. Each individual in this dataset has a longitudinal weight for the probability that he or she remains in the sample. Unfortunately, I have not found an argument to use weights in the plm function? I tried ?weights=? like in standard lm or in nlme or lm4 but it does not work. I asked the

Hi! I am quite a new user of R. I wanted to ask if there was some package for dynamic panel analysis (with Arneallo-Bond Method) like stata. PLM is for panel analysis but not for dynamic. Best regards, Tanveer

Hello, I have a large data matrix (68x13112), each row corresponding to one observation (patients) and each column corresponding to the variables (points within an NMR spectrum). I would like to carry out some kind of clustering on these data to see how many clusters are there. I have tried the function clara() from the package cluster. If I use the matrix as is, I can perform the clara

The thread "R licensing query" currently running has raised the classic critcisms of using Excel for statistics. I was wondering: Has anyone applied the same or similar set of tests to OpenOffice "calc"? Or would the Executive Summary be: "Calc is just like Excel"? (Not that I'm a spreadsheet user, if I can avoid it; but I sometimes get asked about such

Dear R-helpers: We have had fun using betareg to fit models with proportions as dependent variables. However, in the analysis of these models we found some wrinkles and don't know where is the best place to start looking for a fix. The problems we see (so far) are that 1. predict ignores newdata 2. anova does not work Here is the small working example: ---------------------------- x