similar to: Stochastic Dominance Analysis

Is there a way of executing SAS codes in R environment?   Peter Maclean Department of Economics UDSM [[alternative HTML version deleted]]

I am estimating Value at Risk using PerfomanceAnalytics package. The?variables are stored in a data frame. I formated the data variables using zoo() and as.xtx() but it is not working. The working example is below. ##########################################################? reguire(zoo) require(PerformanceAnalytics) reguire(xts) ? year<- c(1991-12-30, 1992-12-30, 1993-12-30, 1994-12-30) R1

I have csv data that extend beyond the area I want for an existing map. I want using the boundaries of the polygon shape file as a cookie cutter so that I can overlay the csv data on map without including anything outside the map boundaries and create a dbf file or shapefile of the clipped data .  The reproducible example: ############################################### library(RColorBrewer)

Hi! A few weeks ago, I have uploaded a new R package "frontier" for Stochastic Frontier Analysis (SFA) [1] to CRAN [2]. It includes the FORTRAN code of Tim Coelli's [3] software "Frontier 4.1" [4]. Hence, the R package "frontier" should have the same capabilities as "Frontier 4.1", i.e. Maximum Likelihood Estimation of Stochastic Frontier Production

Hi! A few weeks ago, I have uploaded a new R package "frontier" for Stochastic Frontier Analysis (SFA) [1] to CRAN [2]. It includes the FORTRAN code of Tim Coelli's [3] software "Frontier 4.1" [4]. Hence, the R package "frontier" should have the same capabilities as "Frontier 4.1", i.e. Maximum Likelihood Estimation of Stochastic Frontier Production

Hi Mackay and anybody (a) Is it possible to select randomly (let say five grids) and plot? (b) Is it possible to plot five nearest grid in one figure? The original question and improved codes: #I am ploting gridded time series data. I would like the actual lat #and lon value appear on the graph-if possible inside the graph as #numbers. If there is also more elegant ways to plot the graphs I

I have data set with binary responses. I would like to conduct polychoric principal component analysis (pPCA). I know there are several packages used in PCA but I could not find one that directly estimate pPCA and graph the individuals and variables maps. I will appreciate any help that expand these reproducible scripts. #How to conduct polychoric principal component analysis pPCA using #either

I need help in indexing grouped data. In this excample (df1 data), the first child had a first immunization at age 2. The second child had the first, second and third immunization at age 5,10, and 12, the third child had first and second immunization at age 4 and 6 and the fourth child had the first immunization at age 2. I have df1 and I need to create df2 with and "ind' variable that

How do I move the legend from default position (right and within the plot)?to the "bottomleft" of the plot? ? interaction.plot(YEAR, ID?GROWTH, legend=TRUE, col = 2:7,xlab="Year", ?????? ylim=c(0,2), ylab="Growth",leg.bty = "o") Peter Maclean Department of Economics UDSM

I am ploting gridded time series data. I would like the actual lat and lon value appear on the graph-if possible inside the graph as numbers. If there is also more elegant ways to plot the graphs I will appreciate more suggestions. ################################# library(ggplot2) library(lattice) month <- c("Jan", "Feb", "Mar", "Apr", "May",

Computational Aspects of Simulation and Inference for Stochastic Processes and the YUIMA Project This two-day workshop is aimed at presenting the latest results on simulation and inference for stochastic processes and their current and prospect implementation within the YUIMA R package. Dates: March 27 (Tue) 9:15-12:15, 14:45-17:45 March 28 (Wed) 9:15-12:15, 14:45-17:45 Location:

Dear R-Users, Is anyone aware of a significance test which allows demonstrating that one distribution dominates another? Let F(t) and G(t) be two distribution functions, the alternative hypothesis would be something like: F(t) >= G(t), for all t null hypothesis: F(t) < G(t), for some t. Best wishes, Matthias PS. This one would be ok, as well: F(t) > G(t), for all t null

Dear all, I want to program my own models about Stochastic Frontier Analysis and Linear programming (Data Envelopment Analysis). In this context, is there anyone that may help me with some simple tutorials and scripts about these issues? Thanks a lot. -- Marcus Vinicius Pereira de Souza, Prof. [[alternative HTML version deleted]]

Hi, I need some help with solving functional equations (Bellman's or Euler's) with numerical methods. I have read the relevant books (Kenneth L Judd: Numerical methods in economics, and some others), but have no practical experience. All the examples in these books are in Matlab, but I would prefer R, since I have been using that for some time and I think that it is generally much nicer

Hi, Given a positive integer N, and a real number \lambda such that 0 < \lambda < 1, I would like to generate an N by N stochastic matrix (a matrix with all the rows summing to 1), such that it has the second largest eigenvalue equal to \lambda (Note: the dominant eigenvalue of a stochastic matrix is 1). I don't care what the other eigenvalues are. The second eigenvalue is

Hi, I am trying to find out the scale efficiency and optimal scale of banks by stochastic frontier analysis given the panel data of bank. I am free to choose any model of stochastic frontier analysis. The only approach I know to work with R is to estimate a translog production function by sfa or other related function in frontier package, and then use the Ray 1998 formula to find the scale

Dear everyone, i`m a german economics student, writing my master´s thesis about "Multivariate Volatility Models". After having read about theoretical aspects of Multivariate GARCH ans Stochastic Volatility Models, I would like to compare DCC-GARCH and DC-SV with help of an empirical application. I figuered out that one has to use MCMC-simulation-methods for that. Some days ago I

Dear all, I am running matrix population models using package "popbio". In a deterministic model {i.e., transition matrix is defined as A <- matrix(c(0.70, 0.70,0.35,0.50), nrow=2,byrow=TRUE}, population growth rate can be estimated from the dominant eigenvalue {command "eigen.analysis"}. However, I cannot figure out the way to compute the asymptotic stochastic population

Dear R-users, a new R package has been released named orddom. This package provides ordinal estimates as alternatives to independent or paired group mean comparisons, especially for Cliff?s delta statistics. It provides basic parameters for various robust tests of stochastic equality with ordinally scaled variables. For two sets of data, ordinal comparison estimates are calculated such as -

Dear R-users, a new R package has been released named orddom. This package provides ordinal estimates as alternatives to independent or paired group mean comparisons, especially for Cliff?s delta statistics. It provides basic parameters for various robust tests of stochastic equality with ordinally scaled variables. For two sets of data, ordinal comparison estimates are calculated such as -