similar to: fitting Ornstein-Uhlenbeck process by MAXIMUM LIKELYHOOD

Is there a package that will allow me to fit Brownian motion and Ornstein?Uhlenbeck models of evolution for discrete traits? I know that geiger and ouch have commands for fitting these models for continuous traits, but these aren't suitable for discrete trait evolution, correct? -- View this message in context:

hello everyone, i'm trying to simulate a 2-parameter integrated ornstein-uhlenbeck (IOU) process, but i'm not sure exactly where to start (which package, which function). the motivation is the paper by taylor et. al. (JASA 1994) "a stochastic model for the analysis of longitudinal aids data." the model they suggest consists of a combination of fixed and random effects, a

dear useRs, i'm working with a mean reverting model of the following specification: y = mu + beta(x - mu) + errorterm, where mu is a constant currently I estimate just y = x (with lm()) to get beta and then calculate mu = estimated intercept / (1-beta). but I'd like to estimate mu and beta together in one regression-step and also get the test-statistics (including parameter

Hi, I'm wondering why the spectrum() phase of quadrature couple isn't purely +/-pi. But mostly, I'm looking for a recommended way to take a 2-D spectrum and convert it into a single complex array. Kindly consider: # 10 Hz sine wave 10 seconds long sampled at 50 Hz deltaT = 1/50 t = seq(0, 10, deltaT) w = 2 * pi * 10 x = ts( sin( w * t ), deltat = deltaT ) y = ts( sin(

Hello, I'm doing some linear regression: >lm<-lm(osas~alp,data) >summary(lm) However, the Rsquared in the output of summary() is not the same as the "standard" Rsquared calculated by spreadsheets, and outlined in statistical guidebooks, being SSR/SSTO. The output says "multiple Rsquared", but it is no multiple regression... What's the difference? Thanks,

Hi, anybody have any ideas on this ? I have two sequences of proportions. Due to conventions in my field, I need to produce a linear correlation between the two. Each sequence of proportions are based upon differing numbers of observations (although within a sequence the number of observations may not fluctuate too much) so it may be necessary/advisable to variance stabilize. Is their a best

--- libcelt/Makefile.am | 6 +- libcelt/bands.c | 26 +++++++++- libcelt/bands.h | 2 +- libcelt/celt.c | 23 +++----- libcelt/pgain_table.h | 133 ------------------------------------------------- libcelt/quant_pitch.c | 117 ------------------------------------------- libcelt/quant_pitch.h | 44 ---------------- 7 files changed, 37 insertions(+), 314

Hi, I'm having problems while working with large data sets with R 1.5.1 in windows 2000. Given a integer matrix size of 30 columns and 15000 rows my function should return a boolean matrix size of about 5000 rows and 15000 columns. First of all I tried to run this function on computer with 256 MB of RAM. I increased memory limit of R with memory.limit() up to 512 MB. I was inspecting

Problem is demonstrated with this code, intended to find the approximate 'x' at which the 'y' is midway between the left and right asymptotes. This particular data set returns NA, which is a bit silly! -------------- sXY <- structure(list(x = c(0, 24, 27, 48, 51, 72, 75, 96, 99), y = c(4.98227, 6.38021, 6.90309, 7.77815, 7.64345, 7.23045, 7.27875, 7.11394, 6.95424)), .Names =

Hi people, I want to obtain the adjusted r-square given a set of coefficients (without the intercept), and I don't know if there is a function that does it. Exist???????????????? I know that if you make a linear regression, you enter the dataset and have in "summary" the adjusted r-square. But this is calculated using the coefficients that R obtained,and I want other coefficients

Dear helpers in this forum, This is a clarified version of my previous questions in this forum. I really need your generous help on this issue. > Suppose I have the following data set: > > id x y > 023 1 2 > 023 2 5 > 023 4 6 > 023 5 7 > 412 2 5 > 412 3 4 > 412 4 6 > 412 7 9 > 220 5 7 > 220 4 8 > 220 9 8 > ...... > Now I want to compute the

I get this error while computing partial correlation. *Error in solve.default(Szz) : system is computationally singular: reciprocal condition number = 4.90109e-18* Why is it?Can anyone give me some idea ,how do i get rid it it? This is the function i use for calculating partial correlation. pcor.mat <- function(x,y,z,method="p",na.rm=T){ x <- c(x) y <- c(y)

Dear Mac users, Hi, as you might have probably read the thread of "[R] Rsquared in summary(lm)" on May 10, it seems that Mac version of lm() seem to be working incorrectly. I enclose the script to produce the result both for lm() and manual calculation for a simple regression. Could you run the script and report with the version of R, so I don't have to go through every builds

Hi All, This is my R-version information:--- > version _ platform i486-pc-linux-gnu arch i486 os linux-gnu system i486, linux-gnu status major 2 minor 7.1 year 2008 month 06 day 23 svn rev 45970 language R version.string R version 2.7.1 (2008-06-23) While calculating partial

Hi I just upgraded to http://svn.xiph.org/trunk/speex r10357 and got this build warning: alfredh@io:$ make -s mdf.o libspeex/mdf.c: In function 'speex_echo_cancel': libspeex/mdf.c:321: warning: statement with no effect libspeex/mdf.c:317: warning: `adapt_rate' might be used uninitialized in this function Is this intentional? In any case here is a simple fix: Index:

Below is a version of [.data.frame that is faster for subscripting rows of large data frames; it avoids calling duplicated(rows) if there is no need to check for duplicate row names, when: i is logical attr(x, "dup.row.names") is not NULL (S+ compatibility) i is numeric and negative i is strictly increasing "[.data.frame" <- function (x, i, j,

Dear all, I wanted to let you know about four phylogenetic comparative methods (PCM) packages that have become available on (3 on CRAN and 1 on GitHub) recently that hopefully will be interesting to somebody. Three of them go significantly beyond the Brownian motion (BM) and Ornstein-Uhlenbeck (OU) processes. 1) There is a new version of mvSLOUCH available. The most important change is that the

Dear all, I wanted to let you know about four phylogenetic comparative methods (PCM) packages that have become available on (3 on CRAN and 1 on GitHub) recently that hopefully will be interesting to somebody. Three of them go significantly beyond the Brownian motion (BM) and Ornstein-Uhlenbeck (OU) processes. 1) There is a new version of mvSLOUCH available. The most important change is that the

Hello. I try to compute a "White-corrected" ANOVA. Therefore I use the command "Anova" implemented in the car()-package): Anova(modelname, white.adjust="hc3") and receive the error message: "Fehler in SS[i] <- SS.term(names[i]) : nichts zu ersetzen" (German) "Error in SS[i] <- SS.term(names[i]) : nothing to replace" (probably being the

Hello, I wanted to set my own time intervals for shutdown. {poweroff,return,paused.return}, so I had to change sources, where it has been set in a hard way. poweroff: Sxx\r return: Zxx\r paused.return: SxxRyyyy\r Solution A: Why not adding an info about these commands in a generic way and issuing shutdown.{poweroff.xx,return.xx,paused.return.xxyyyy} Solution B: Why not creating a special