similar to: Restricted VAR parameter estimation

Dear List, This is just a programming problem which i cannot seem to figure out. I am trying to get a set of power from a test (say, kolmogorov smirnov) out of a distribution (say, G-K distribution) as follows. I am trying to reduce to pain of writing the whole set of data points (p# below) using "for" loop. However, I seem to have some problem in it as the output "M" does not

When using the PLM package (version 1.2-8), I encounter the probem that calling the FGLS estimator evokes strange behavior, when choosing the "random" effects model. After calling the PGGLS function to estimate FGLS, PLM gives me a warning, stating that the "random" model has been replaced with the "pooling" model. I would, however, really like to estimate the random

Hello, I am currently testing a Vector AR of dim 3 over not a lot of data (135 * 3 observations) . To test the adequation of my vecot ar, I use the Schwarz Bayesian Criterion and the classic modified Portmanteau test on the residuals (it can be found for instance in http://www.iue.it/PUB/ECO2004-8.pdf , page 15) -> the null hypothesis is "the residuals process are a vectorila white

Hi, I am trying to write a simulation of the movements of four animals between six patches. The movement between patches is based on a first-order Markov chain so that the next patch they visit depends on the patch they were in before. I have written code that allows me to simulate the movement of one animal but when I add more there seems to be a problem and all chains come back as N/A. I can

Hi list members I have a vector of strings x=c("w","ex","ee") And I want to get a logical vector showing the positions where my search string "e" matches the elements partially, i.e. is at least the left-hand part of the target strings, i.e. I want to get a vector FALSE TRUE TRUE. Any ideas? Thanks Steve Powell proMENTE social research research |

Dear all, S+Finmetrics has a number of very specilised functions. I am particularly interested in the estimation of cointegrated VARs (chapter 12 of Zivot and Wang). In this context the functions coint() and VECM() stand out. I looked at package "dse1", but found no comparable functionality. Are there any other packages you could point me to? In general, are there efforts for

Hi ,everyone. I want to draw a boxplot figure, main script shown as below. when I run the command "boxplot(bjavee~yearname)",it is wrong with the error information " model.frame.default(formula = bjavee ~ yearname) : variation 'bjavee' list is wrong". I want to add the yearname as the x-axis tick. And yearname is a array with the length 12,while bjavee is a 5*12

I am fitting a reduced form VAR model using VAR in the vars library. I have several endogenous variables, and two exogenous variables. I would like to explore the effects of a shock to one of the exogenous variables on one of the endogenous variables. Using irf in the vars library only calculates the irf for the endogenous variables, this is obviously by design, is there some theoretical

Hi there, I'm trying to solve 2 nonlinear equations in 2 unknowns using the BB package. The first part of my program solves 3 ODEs using the deSolve package. This part works. The output is used as parameter values in the functions I need to solve. The second part is to solve 2 equations in 2 unknowns. This does not work. I get the error message "unexpected end of input". So what

Readers, I have a data set as follows: 1,1 2,2 3,3 4,4 5,3 6,2 7,-10 8,-9 9,-3 10,2 11,3 12,4 13,5 14,4 15,3 16,2 17,1 I entered this data set using the command 'read.csv'. I want to exclude values fewer than zero in column 2 so then I tried the following command: boxplot.stats(x[>0,2],do.conf=FALSE) Error: syntax error, unexpected GT, expecting ',' in

I'm new to R and some what new to the world of stats. I got frustrated with excel and found R. Enough of that already. I'm trying to test and correct for Heteroskedasticity I have data in a csv file that I load and store in a dataframe. > ds <- read.csv("book2.csv") > df <- data.frame(ds) I then preform a OLS regression: > lmfit <- lm(df$y~df$x) To

Dear WizaRds, having met some of you in person in Vienna, I think even more fondly of this community and hope to continue on this route. It was great talking with you and learning from you. Thank you. I am trying to work through an artificial example in post stratification. This is my dataset: library(survey) age <- data.frame(id=1:8, stratum=rep(

Hi R-Help! I am trying to find a nicer way of extracting all the "complete" diagonals of a matrix. I am working with very large matrices that have many more rows than columns. I want to be able to extract each of the diagonals that are as long as the number of columns in the matrix. I have written a rather ugly function that presently does the job. It illustrates what I am trying to

Estimada comunidad tengo un problema del que no encuentro datos que me ayuden mucho en la web. Estoy haciendo calculos por grupos con data,table. Tengo un archivo (zp.res) con tres columnas que clasifican los datos (sol, con, dia) y una columna de datos numericos (media), de la siguiente forma: sol con dia media 1: con 0 1 -22.6 2: con 0 1 -36.6 3: con 0 1 -35.6 y

This includes two kernel patches, scsi-target and IO_CMD_EPOLL_WAIT. The former is a modified version of the scsi target infrastructure in mainline. The latter enables applications to handle AIO and non-AIO fds in the same loop. blktap uses the different patch, AIO event queue patch for the same aim. The IO_CMD_EPOLL_WAIT patch will be merged into mainline (and the AIO event queue will not) so

Hello, a have two matrices of data as below. I would like to add-up the duplicate in terms of pair of names in rows, and then merge the values in the second matrix to the pairs as two new variables x3 and x4. Input ,x1,x2 jane.mike,31,43 jane.steve,32,2 jane.steve,5,3 jim.mike,76,5 jane.steve,4,4 mike.steve,54,7 mike.steve,5,7 jane.mike,7,8 and ,y jane,0.3 jim,0.4 mike,0.1 carl,0.5 john,0.9

Hello Everyone,   This is my first attempt to do something in R. As a precursor to a Willingness to Pay analysis, I want to conduct a Mixed Conditional Logit analysis but am unsure how to proceed because of some nesting within my data.   Below is some data and code that illustrate what I’m trying to do. The data are based on responses to a conjoint survey obtained during pilot testing. In the

Hi there, According to ?par, 'font' is an integer which specifies which font to use for text, that 1 corresponds to plain text (the default), 2 to bold face, 3 to italic and 4 to bold italic. When I test Chinese character in pdf(), I found that 1 to bold face, 2 to italic, 3 to bold italic, 4 to symbol. and I don't find how to set plain text. In the following code, the font to use

Hi all Can anybody help me with this? I am trying to include in an automatic way the argument in arg.names in a barplot. I generate the labels I want to appear below the bars with a for loop, and they contain subscripts, so I need to use expression anch<-0.05 esp<-4 for (i in 1:dim(Ntot)[1]) { naux<-Ntot[i,] naux2<-naux[naux>0] nind<-which(naux>0)

Hi, I would like to evaluate a function f(x,y) taking two vectors as entries on all pairs of X rows and Y rows, where X and Y are n-by-p and m-by-p matrices respectively. Of course, I would like to avoid loops if possible, as the dataset I want to process is quite large. I was not able to find a combination of outer() and apply() to do this -- note that I am fairly new to R. Below is