similar to: books on Time series

Hi all, simple Q: how do I extract the upper and lower CI for predicted probabilities directly for a glm - I'm sure there's a one line to do it but I can't find it. the predicted values I get with the predict (.. "response") Thanks Gerard ********************************************************************************** The information transmitted is intended only for

dhabby wrote: Last week I run in to a lot a problems triyng to fit an ARIMA model to a time series. The problem is that the internal process of the arima function call function "optim" to estimate the model parameters, so far so good... but my data presents a problem with the default method "BFGS" of the optim function, the output error looks like this:

HI, I'd like to perform a weighted linear least squares fit with R on data with varying errors on both vectors. I can do this with one axis using lm, but have no idea where to go from here. I've tried googling, but no idea. Any suggestions? Thanks, James

Hi all, I have a multiple queing situation I'd like to simulate to get some idea of the distributions - waiting times and allocations etc. Does R has a package available for this - many years ago there used to be a language called "simscript" for discrete event simulation and I was wondering if R has an equivalent (or hopefully with graphics, something better!). Apologies if there

Dear List, Please find a frank interview with Phil Rack, creator of Bridge to R ( from both SAS and WPS interfaces). For those unaware of WPS- it is basically a SAS language compiler (read SAS code,writes SAS code,Reads and writes SAS datasets) ,priced at 660 $ a licence ( or estimated 10 times cheaper than Base SAS. The UK based WPC held, WPS doesnt have advanced statistical facilities like

What function and package I use to conduct ordinal regression?? My data is composed 2colums and 180rows. The first colum indicate level of mass and second colum is intensity. So, I want to calculate how much intensity are related mass. [[alternative HTML version deleted]]

Dear all, I've replicated the cheese tasting example on p175 of GLM's by McCullagh and Nelder. This is a 4 treatment (rows) by 9 ordinal response (cols) table. Here's my simple code: #### cheese library(MASS) options(contrasts = c("contr.treatment", "contr.poly")) y = c(0,0, 1, 7, 8,8,19, 8,1, 6,9,12,11, 7,6, 1, 0,0, 1,1, 6, 8,23,7,

Hi all, apologies if this is obvious - but I can't see it and would appreciate some quick help! the matrix mhouse is 26x3 and I'm computing odds ratios. The simple code below "should" compute the odds vector for every pair (325) i.e. 26C2 in cols 1 and 2. On the first i=1 outer loop the inner j loop runs from 2 to 26 ok and then I get the error (Error: subscript out of bounds)

Hi! I have two time series. Both measure the same thing and I would like to determine which one is noisier. Would it be a good measure of the noise in each time series the absolute lag difference? Is this a good measure? Any other measure I could use? Thanks for help :) David Riano Center for Spatial Technologies and Remote Sensing (CSTARS) University of California 250-N, The Barn One Shields

Hi list, I would like to normalize a matrix (two actually for comparison) using iterative proportional fitting. Using ipf() would be the easiest way to do this, however I can't get my head around the use of the function. More specifically, the margins settings... for a matrix: mat <- matrix(c(65,4,22,24,6,81,5,8,0,11,85,19,4,7,3,90),4,4) using fit <-

Is Pearson's Chi-Square test for contingency tables asymptotically unbiased for large tables (large degrees of freedom) regardless of the expected values in each cell? The rule of thumb is that Pearson's Chi-square should not be used when large numbers of cells have expected values < 5. However, I compared the results on 4x4 contingency tables for R's chisq.test using chi-square

Dear R experts and statisticians, I have some time series datasets, they are several years vegetation indices (about 50 data points per year) sampled from different station. These indices have similar dynamics with seasonal change. My questions are, 1) How can I compare the difference among the indices, and how can I say there is significant differnce between two time series. They

Hello, Anyone who knows a fast and accurate algorithm for generating draws from an underdispersed Poisson distribution. Or even better, if there is a package containing such an implementation. Thanks Rene

Hello, Guys: I'm from China, my English is poor and I'm new to R. The first message I sent to R help meets some problems, so I send again. Hope that I can get useful suggestions from you warm-hearted guys. Thanks. I builded a multiplicative seasonal ARMA model to a series named "cDownRange". And the order is (1,1)*(0,1)45 The regular AR=1; regular MA=1; seasonal AR=0; seasonal

I am a beginner in using R and I need help in the interpretation of AR result by R. I used 12 observations for my AR(2) model and it turned out the intercept showed 5.23 while first and second AR coefficients showed 0.40 and 0.46. It is because my raw data are in million so it seems the intercept is too small and it doesn't make sense. Did i make any mistake in my code? My code is as follows:

Dear all, sorry to bother you all with this but I've been trying to use the loglm in MASS package (v2.8.0) and cannot get any sensible output. I'm wondering am I doing something very foolish or missing something obvious. For example, I tried the documentation help(loglm) example - here's the code # Case 1: frequencies specified as an array. sapply(minn38,

Dear all, I have the following dataset: each row corresponds to count of forest floor small mammal captured in a plot and vegetation characteristics measured at that plot > sotr plot cnt herbc herbht 1 1A1 0 37.08 53.54 2 1A3 1 36.27 26.67 3 1A5 0 32.50 30.62 4 1A7 0 56.54 45.63 5 1B2 0 41.66 38.13 6 1B4 0 32.08 37.79 7 1B6 0 33.71 30.62

If anyone wants to see a prime example of how inefficient it is to program in SAS, take a look at the SAS programs provided by the US Agency for Healthcare Research and Quality for risk adjusting and reporting for hospital outcomes at http://www.qualityindicators.ahrq.gov/software.htm . The PSSASP3.SAS program is a prime example. Look at how you do a vector product in the SAS macro

Hello, I am trying to collect several global measures or statistics for time-series as well as packages of R that can compute them. I have found several of them in papers and books, but the literature is so big i am sure i am missing several of them. skewness kurtosis min max mean SD trend seasonality periodicity chaos (Lyapunov Exponent) / Largest Lyapunov Exponent (i think is the same

Hello, I am totally new in the field of time series analysis and forecasting and R. I read that R is a powerful tool for time series. Could anyone give me navigation what models of time series are availiable in R etc? -- View this message in context: http://r.789695.n4.nabble.com/Time-Series-Analysis-and-Forecasting-tp4646637.html Sent from the R help mailing list archive at Nabble.com.