similar to: simulation study using R

Hello All, I was wondering how I can get the overall Pearson chi^2 test of model fit with its df and p value in the LTM package for the 2PL models. Thanks, -- Davood Tofighi Department of Psychology Arizona State University [[alternative HTML version deleted]]

Hello, II used the logLik() function to get the log-likelihood estimate of an object. The function also prints the degrees of freedom. How can I extract the degrees of freedom and assign it to a variable. Below is the output: > logLik(fit2pl) 'log Lik.' -4842.912 (df=36) Thanks, Davood Tofighi [[alternative HTML version deleted]]

Davood, I developed an MC simulation model for wind hazard analysis last year. I found three important issues to increase efficiency: 1) Reuse most variables in each loop 2) Write results (1000 stats) to external files, perhaps one file for each condition. (a good ID for each file can be implemented using "paste") 3) Develop a function to process the results stored in the external

Dear All, I have a function f(x,y,z)=exp(x^3+y^4+x^2*y+x*z^2+y/z) over D, where is D={ (x,y,z)| 0 <z<Inf, 0<y<c1*z, 0<x<c2*/y}. x,y,z are all vectors and c1 and c2 are constants. I tried the "adapt" package and I get some error. This is the error message: "Error in function (z, y, x) : argument "x" is missing, with no default" I included my R

Hello, I'm using filehash on the windows XP and it has been working fine with the newest R version 2.6.2. However, on the windows vista, when I ran the same code, I got the following error: > dbCreate("simdb") #create simdb database [1] TRUE > db<-dbInit("simdb") #initiate an object of database Error in sprintf(gettext(fmt, domain = domain), ...) : object

Hard to follow data analysis without data. Try making your example reproducible [1][2][3] and post in plain text (a setting in your emailer). Read the Posting Guide mentioned in the footer to avoid other posting pitfalls. [1] http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example [2] http://adv-r.had.co.nz/Reproducibility.html [3]

hello, I have a graph and i use qgraph package to calculate centrality parameters. Now I want to know the maximum value of shortest path for each vertex with discarding the Inf value in short pathes. For this I use the ShortestPathLengths of centrality function in qgraph. but when I want to get the maximum the result is wrong. here is my code: cen<-centrality(Q)

Refinement of the schema.xml (below) THis however does not solve the "no results" and "Out of range" errors in Dovecot and Solr <?xml version="1.0" encoding="UTF-8"?> <schema name="dovecot" version="2.0"> <uniqueKey>id</uniqueKey> <fieldType name="booleans" class="solr.BoolField"

Okay, here is a more complete example: sample_sizes<- matrix(c(10,10,10,25,25,25,25,50,25,100,50,25,50,100,100,25,100,100), nrow=2) # see what it looks like sample_sizes ssds<-c(4,4.4,5,6,8) nssds<-length(ssds) results<-list() # first loop steps through the sample for(ss in 1:dim(sample_sizes)[2]) { # get the two sample sizes ss1<-sample_sizes[1,ss] ss2<-sample_sizes[2,ss]

hello, I have a problem in how to generate data in a simulation study. I have a logistic model to evaluate p by 3 covariates. I need to generate 4 variables: the binary outcome Y and 3 covariates: gender (binary) and aps and tiss (continuous variables). I have the logistic model which is the expected model: log(p(y=1)/(1-p(y=1))=-1.659-0.05*sex+0.063*aps+0.04*tiss0) I generate the outcome y like

Dear R community,and especially Giovanni Millo, For my master's thesis i need to simulate a panel data with the fixed effects correlated with the predicor, so i run the the following code: set.seed(1970) #######################Panel data simulation with alphai correlated with xi##################################### n <- 5 t <- 4 nt <- n*t pData <- data.frame(id =

Here I am in a simulation study where I want to find different values of x and y such that f(x,y)=c (some known constant) w.r.t. x, y >0, y<=x and x<=c1 (another known constant). Can anyone please tell me how to do it efficiently in R. One way I thought that I will draw different random numbers from uniform dist according to that constraints and pick those which satisfy f(x,y)=c. However

hi, i am new in this field. do favorite<http://stackoverflow.com/questions/36404707/simulation-study-of-2-sample-test-on-different-combination-of-factors#> If I wish to conduct a simulation on the robustness of two sample test by using R language, is that any ways in writing the code? There are several factors (sample sizes-(10,10),(10,25),(25,25),(25,50),(25,100),50,25),(50,100),

Dear R helpers Suppose I have a portfolio of securities with exposure to Equity, Bonds and Forex (say $ 1000000 each). Is there any fucntion in R that will help me calculate Value at Risk (VaR) using Monte carlo Simulation , Historic simulation and Variance - Covariance Simulation. With regards Maithili

You have quite a few mistakes in your example. The code below works for me - you can wrap it in a function if you like. I think you will need a lot more practice before you can write something like this in R as you are missing close braces and haven't really worked out the difference between the number of calculations you are doing for each replication and the number of replications. It takes

Hello. I have tested such form: <form method=''POST''> <input type=''hidden'' name=''myfield'' value=''value1''> <input type=''hidden'' name=''myfield'' value=''value2''> <input type=''submit'' name=''_submit''

Hello, How can I make a monte carlo simulation on R? Regards Adel -- PhD candidate in Computer Science Address 3 avenue lamine, cité ezzahra, Sousse 4000 Tunisia tel: +216 97 246 706 (+33640302046 jusqu'au 15/6) fax: +216 71 391 166 [[alternative HTML version deleted]]

Hi, i think i have figured the purpose of using this index (i-1)*5+j in the previous example that you gave. It is because that i have to consider the outer loop and inner loop also... so the iterative for i need to minus one because it have ran one times simulation already ,then times the number of sizes of inner loop, then plus the iterative of j.... then for the simulation, i think there will

Hi, R-helpers, I'm trying to use R to do a Monte Carlo simulation and need the help. What I have is a matrix that consists of the probabilities for the persons to choose zones. For example, in the matrix shown below, each column represents a person, and each row represents a zone. So, the probability that the first person will choose the 2nd zone is 30%. 25% 30% 10% 30% 20% 0% 20% 50% 60%

Dear R user: I wonder if it is possible to run monte carlo simulation with dse2 package(MonteCarloSimulations function) using ordinary differential equation. How do I define the model? Or if there are any functions which can run monte carlo simulation using ordinary differential equation. Please give me some comments. Thanks in advance!!