similar to: correlating irregular time series

>Message: 41 >Date: Sun, 08 Jan 2006 13:52:33 +1100 > From: paul sorenson <sourceforge@metrak.com> >Subject: Re: [R] Wikis etc. >To: Frank E Harrell Jr <f.harrell@vanderbilt.edu>, r-help > <r-help@stat.math.ethz.ch> >Message-ID: <43C07E71.3040303@metrak.com> >Content-Type: text/plain; charset=ISO-8859-1; format=flowed > >Frank E Harrell Jr

I am trying to replace a spreadsheet model of a project justification with an R script. I can't seem to track down R functions to calculate Internal Rate of Return and NPV? Am I missing something? NPV doesn't seem so difficult to calculate (at least for a regular series) but I am struggling to identify how to solve for IRR in R. It would be sufficient if it worked for a regular

Hello I have trouble getting my original datetime back see below. I hope I am missing something. Please help. > tt <- as.POSIXct("2011-01-07 07:49:13", tz="EST") > tt [1] "2011-01-07 07:49:13 EST" > ttn <- as.numeric(tt) > ttn [1] 1294404553 > tt <- as.POSIXct(ttn,origin='1970-01-01',tz="EST") > tt [1] "2011-01-07

--- python/t/590-aio-copy.py | 122 +++++++++++++++++++++++++++++++++++++++ 1 file changed, 122 insertions(+) diff --git a/python/t/590-aio-copy.py b/python/t/590-aio-copy.py new file mode 100644 index 0000000..129dde1 --- /dev/null +++ b/python/t/590-aio-copy.py @@ -0,0 +1,122 @@ +# libnbd Python bindings +# Copyright (C) 2010-2019 Red Hat Inc. +# +# This program is free software; you can

v1 was here: https://www.redhat.com/archives/libguestfs/2019-August/msg00103.html In v2 I've made several changes: - Fix Python callbacks so if they don't return something which is int-like, we assume they mean to return 0. - Add nbd.Buffer free() method. Read commit message in patch 2 to see what this is about. - Fixed the asynch copy test to deal with the unbelievably

Hello, I have a survivor curve that shows account cancellations during the past 3.5 months.  Fortunately for our business, but unfortunately for my analysis, the survivor curve doesn't yet pass through 50%.  Is there a safe way to extend the survivor curve and estimate at what time we'll hit 50%? We started a new program 3.5 months ago, and I believe that this set of accounts behaves

Basically the same as this patch series, but for Python: https://www.redhat.com/archives/libguestfs/2019-August/msg00235.html plus adding the 590 asynch test at the end. Rich.

Dear list users, I need to learn about MCMC methods, and since there are several packages in R that deal with this subject, I want to use them. I want to buy a book (or more than one, if necessary) that satisfies the following requirements: - it teaches well MCMC methods; - it is easy to implement numerically the ideas of the book, and notation and concepts are similar to the corresponding R

Hello, I am looking for documentation (PDF ?) about doing clustering with the EM Algorithm on R... I'm sorry for this question which may be trivial... Thanks... Dominique

Hi, list, Sorry if I am bothering you. I am interested in using xgrid with R for distributed computing. I am using MacOS X and my R 2.1. 1 is already installed and running. The client computers are all of the same type and the same version of R has been installed on them. We have also set up xgrid on my system and client computers as well. I am wondering if any one can give me some clues

Hello, I've got to compute a minimization equation under an equality constraint (Min g(x1,x2,x3) with x1+x2=const). The Constroptim function does not authorize an equality condition but only inequality conditions. Which function can I use instead? Thank you very much for your help. Gael Robert - +33 1 42 14 27 96 ****************************************************************** This

Hi all, I'm trying to estimate a nested model (purchase decision, cloglog formula, & quantity bought given a purchase, truncated Poisson). Some of the parameters are mixed (6) and 4 are fixed for all the respondent. The simulated ML (500 simulations) method forwards highly correlated estimates. After some research, Hybrid Monte Carlo seems to be a good alternative to estimate the model. I

Dear R users, I need to to the the following. Let a= 1 2 3 4 5 6 and b= -1 -2 -3 be (2x3) matrices. -4 -5 -6 I need to combine the two matrices into a new (2x6) matrix like this: ab = ( 1 -1 2 -2 3 -3 ) 4 -4 5 -5 6 -6 How can this be done in R? ----------------------------------------------------------------- ?????? ???

Full_Name: Reinhold Bader Version: 2.1.0 OS: SLES 9 Submission from: (NULL) (129.187.48.1) I tried to build R using the Intel compilers (icc, ifort) and the Math Kernel Libraries for BLAS/LAPACK Optimizations used were -O3, and the FPICFLAGS="-fpic" was exported. The build failed with the following error message: ... dumping R code in package 'methods' Saving namespace image

Hi, I am trying to convert the following NLMIXED code to NLME, but am running into problems concerning 'Singularity in backsolve'. As I am new to R/S-Plus, I thought I may be missing something in the NLME code. NLMIXED *********** proc nlmixed data=kidney.kidney; parms delta=0.03 gamma=1.1 b1=-0.003 b2=-1.2 b3=0.09 b4=0.35 b5=-1.43 varu=0.5; eta=b1*age+b2*sex+b3*gn+b4*an+b5*pkn+u;

Hi all I have a data set of the following format. 0 0.7087872E+06 5 0.7087872E+06 10 0.7087872E+06 15 0.7087872E+06 20 0.7087872E+06 25 0.7087872E+06 30 0.7087872E+06 35 0.7087872E+06 I was trying to read in this file and plot it. leg16<-read.csv("wwleg16.ttn",sep=" ", dec=".", header =F) But leg16 holds all

Dear R users, Please can you help me with a relatively straightforward problem that I am struggling with? I am simply trying to plot a baseline survivor and hazard function for a simple data set of lung cancer survival where `futime' is follow up time in months and status is 1=dead and 0=alive. Using the survival package: lung.wbs <- survreg( Surv(futime, status)~ 1, data=lung,

Hi all, Issue: I have two datasets, one is a regular time series (rain gauge) with resolution of 10 minutes. The other one is an irregular time series (link). Now I want to analyze the correlation between these two datasets with linear regression. The regular time series is a data.frame and the irregular time series is a zoo object. Problem: For the irregular time series (link) I want also a 10

Hello, I am having trouble constructing a time series object for my data. This is because the frequency is irregular: one year, there may be only 100 individuals, another 200. There are 100 measurements for every individual. I have the observations in a data frame with the year that they were taken from as a factor. I would like to plot the top 10 mean measurements for each year and connect them

Dear R users, I am using the vars package to calculate the impulse response functions and the forecast error variance decomposition of a VAR model. Unfortunately I do not know whether these functions assume unit or one standard deviation shocks. I tried to look into the code of these functions, but in vain: neither irf, nor vars::irf, nor vars:::irf output the code of the functions. Does someone