similar to: Baysian model averaging method

Hi List, I am new to this Rsoftware, i want to make a sereis for example which is having values like this, s<- 0,0.1,0.2,0.3,0.4........,1 i tryed this statement s<-0:0.1:1 but this giving an error megssage. but by default increment 1 it is taking ,,,,,so what to do ,, i want to use this varible in for loop.. like for(j in s) thanks in advance ANIL KUMAR( METEOROLOGIST) LRF

Dear R users, i am using locfit package developed by loader in R software, my problem is that as i am doing independont forecast using locfit object , i am able to do independont forecast for more than one years simultaniously. But when i am doing one year forecast(single) this code is giving following error... "Warning message: 'newdata' had 1 rows but variable(s) found have 24

Hi, List , i have 6 predictor variables and i want to make possible combinations of these 6 predictors ,all the data is in matrix form , if i am having 6 predictors than possible combination of sets are 64 2 power 6, or 63 ,whatever it may be i want to store the result in another variable to each combination and that i want to put in some model , i want to put every combination in some model

  Hello list, i have a very simple question about matrix assignment. i did like this. res<-1:30 dim(res)<-c(5,6) ind<-1:6 now i want to assign the value of this variable ind to first coloumn in matrix res. like res[,1]<-ind but this code is giving error , Actualy i have a for loop and value of ind variable is changing every time ,,total 6 times,,i want to assign every vlaue

&nbsp; Hi, List ,I am searching any package on R which can do wavelet filtering for mother wavelet morlet ,is anybody having any script for the same ? I am new to the RwAVELET ANALSSIS.. THANKS IN ADVANCE ANIL KUMAR ANIL KUMAR(&nbsp;METEOROLOGIST) LRF SECTION&nbsp; NATIONAL CLIMATE&nbsp;CENTER ADGM(RESEARCH) INDIA METEOROLOGICAL&nbsp;DEPARTMENT

Hi List, I have a time series of 122 values, actualy it is a time series of daily indian monsoon rainfall. now i want to filter this time series for a particular oscilation say 10 to 20days oscilation. i want to find out what amount of variance is explained by this mode. Which package is available in R for this purpose. and how to calculate nquest frequancy of this series. any help is much

HI LIST i am a new R user, i am trying to make a model,which will give me output in probability,which will take predictors and predictand serie as input and and give me output in terms of probability(e.g below normal,normal,above normal etc.).What is the package and what is the function for probability model.What are the possible methods for fitting such type of model,and what is the

Hi List, I am new to this Rsoftware, i want to make a sereis for example which is having values like this, s<- 0,0.1,0.2,0.3,0.4........,1 i tryed this statement s<-0:0.1:1 but this giving an error megssage. but by default increment 1 it is taking ,,,,,so what to do ,, i want to use this varible in for loop.. like for(j in s) thanks in advance with regards anil kumar ANIL

Dear R users and developers After upgrading to Windows XP and R 1.9.1 and 2.0, I retried to execute plot.baysian() to a data set that I had used previously to plot with no problem in win2000 R1.8. The error I get is: Error in points(Mbar[-index], lods[-index], pch = ".") : only 0's may mix with negative subscripts Thanx in advance Dino P.S. I allready sent this message

Hi, I have a small doubt regarding naive Bayes. I am able to classify the data's properly but i am just stuck up with how to get the probability values for naive bayes. In the case of SVM we have "attr" function that helps in displaying the probability values. Is there any function similar to "attr" in naive Bayes that can be used for displaying the attribute values. my

Hi there, two questions. 1) Is there any possibility to look up the help pages within R for more complex combinations of character strings, for example "Bayesian" AND "regression" but not necessarily "Bayesian regression"? 2) Is there a package/command that does fully Bayesian linear regression (if possible with variable selection)? Thanks, Christian *** --- ***

The article on BMA (Bayesian model averaging) presents most valuable tools for model selection, but I find one detail confusing in Example 1. In page 4 of RNews 5/2, second paragraph says that the probability of Time variable not being in the model is 0.445. It seems to me that the figure should be 1 - 0.445 = 0.555, because p!=0.445 is the prob. of Time variable being in the model. The plot in

Hello R Group, Below is the code I submit: library("BMA") X <- read.table("C:/Documents and Settings/Administrator/Desktop/coding.txt",header=TRUE) Y <- read.table("C:/Documents and Settings/Administrator/Desktop/1DCS.txt",header=TRUE) IGout<- iBMA.glm(X, Y, glm.family= gaussian(), verbose = TRUE, thresProbne0 = 5 ) summary(IGout) IGout I

R lets one lock an environment with both an R function, base::lockEnvironment, and a C function, R_LockEnvironment, but, as far as I can tell, no corresponding function to unlock an environment. Is this omission on principle or just something that has not been done yet? I ask because several packages, including the well-used R6 and rlang packages, fiddle with some bits in with SET_ENVFLAGS and

Hello Chris,  I 've found two other issues  with MAE and CRPS, giving warning  when running examples. I've the same issue on my data.  Hope that you could find some time to take a look here. Thank you Anna > library(ensembleBMA) Loading required package: chron > example(MAE) MAE>   data(ensBMAtest) MAE>   ensMemNames <-

Hello everybody, In order to predict income for different time points, I fitted a linear model with polynomial effects using BMA (bicreg(...)). It works fine, the results are consistent with what we are looking for. Now, we would like to predict income for a future time point t_next and of course draw the prediction interval around the estimated value for this point t_next. I've found the

Robust Covariance Estimation Software via Nearest Neighbor Variance Estimation (NNVE) Software to carry out robust covariance estimation by Nearest Neighbor Variance Estimation (NNVE) [Wang and Raftery (2002, J. Amer. Statist. Ass.)] is now available for R and Splus. In the simulation studies published in JASA, this had mean squared error at least 100 times smaller than that of other leading

Robust Covariance Estimation Software via Nearest Neighbor Variance Estimation (NNVE) Software to carry out robust covariance estimation by Nearest Neighbor Variance Estimation (NNVE) [Wang and Raftery (2002, J. Amer. Statist. Ass.)] is now available for R and Splus. In the simulation studies published in JASA, this had mean squared error at least 100 times smaller than that of other leading

Hello! I have data containing a large number of probabilities (about 60) of nonzero coefficients to predict 10 different independent variables (in 10 different BMA models). i've arranged these probabilities in a matrix like so: (IV1) (IV2) (IV3) ... p(b0) p(b0) p(b0) p(b1) p(b1) p(b1) p(b2) p(b2) p(b2) ... where p(b1) for independent variable 1 is p(b1 !=

Dear friends, In R, the help of "bic.glm" tells the difference between postmean(the posterior mean of each coefficient from model averaging) and condpostmean(the posterior mean of each coefficient conditional on the variable being included in the model), But it's still unclear about the results explanations, and the artile of Rnews in 2005 on BMA still don't give more detail on