similar to: how to evaluate a dynamic variable?

Dear List, Below is a simple, standard loss model that takes into account the terms of an insurance policy: deductible <- 15 coverage.limit <- 75 insurance.threshold <- deductible + coverage.limit tmpf <- function() { loss <- rlnorm(rpois(1, 3), 2, 5) sum(ifelse(loss > insurance.threshold, loss - coverage.limit, pmin(loss, deductible))) } net <- replicate(1000000, tmpf())

I would like to be able to randomise presence-absence (i.e. binary) matrices whilst keeping both the row and column totals constant. Is there a function in R that would allow me to do this? I'm working with vegetation presence-absence matrices based on field observations. The matrices are formatted to have sites as rows and species as columns. The presence of a species on a site is

Hello! I have a data frame A (below) with a grouping factor (group). I take my DV and create the new, lagged DV by applying the function lag.it (below). It works fine. A <- data.frame(year=rep(c(1980:1984),3), group= factor(sort(rep(1:3,5))), DV=c(rnorm(15))) lag.it <- function(x) { DV <- ts(x$DV, start = x$year[1]) idx <- seq(length = length(DV)) DVs <- cbind(DV, lag(DV,

Dear guRus, I am trying to replace "~" by "$\sim$" for TeX. However, I can't get the backslash to work. I would like to turn "DV~IV" into "DV$\sim$IV". sub("~","$\sim$","DV~IV") => "DV$sim$IV" sub("~","$\\sim$","DV~IV") => "DV$sim$IV"

Hello! I have 2 variables - predictor "pred" and response variable "DV": pred<-c(439635.053, 222925.718, 668434.755, 194242.330, 5786.321, 115537.344, 100835.368, 7133.206, 159058.286, 4079991.629, 3380078.060, 2661279.136, 2698324.478, 1245213.965, 1901815.503, 1517019.451, 1396857.736, 1034030.988, 432249.574, 342329.325, 1831335.792, 2209578.859, 1641709.754,

This is a simple problem that has stumped me: I'm trying to loop through a few dozen variable names in graphs. I've tried various approaches like this: attach(mydata) ivs <- c("oneiv", "anotheriv", "yetanotheriv") dvs <- c("onedv", "anotherdv", "yetanotherdv") for (iv in ivs) { for (dv in dvs) { graphname <- paste(iv,

I wonder if someone could explain the behavior of the anova() and lm() functions in the following situation: I have a standard 3x2 factorial design, factorA has 3 levels, factorB has 2 levels, they are fully crossed. I have a dependent variable DV. Of course I can do the following to get the usual anova table: > anova(lm(DV~factorA+factorB+factorA:factorB)) Analysis of Variance Table

Dear all, I have a function that predicts DV based on one predictor pred: pred<-c(0,3000000,7800000,15600000,23400000,131200000) DV<-c(0,500,1000,1400,1700,1900) ## I define Function 1 that computes the predicted value based on pred values and parameters a and b: calc_DV_pred <- function(a,b) { DV_pred <- rep(0,(length(pred))) for(i in 1:length(DV_pred)){ DV_pred[i] <- a *

I took the first two lines of the sample program in the tutorial: hendrik at lovesong:~/dv/lang/hlvm$ cat broken.cpp #include "llvm/DerivedTypes.h" #include "llvm/Module.h" hendrik at lovesong:~/dv/lang/hlvm$ and tried to compile them using the llvm-dev in Debian testing: hendrik at lovesong:~/dv/lang/hlvm$ g++ -o broken.o -c broken.cpp In file included from

Hello, this is a follow up on my previous inquiry regarding the use of the map library (Becker and Wilks 1993). Using the 'world' database I would like to draw filled countries in a world map so that the filling colors of each country corresponds to the value of a policy variable "fix.float" at a specific "year" (the goal is to visualize a policy diffusion pattern

# I've tried to make this easy to paste into R, though it's probably so simple you won't need to. # I have some data (there are many more variables, but this is a reasonable approximation of it) # here's a fabricated data frame that is similar in form to mine: my.df <- data.frame(replicate(10, round(rnorm(100, mean=3.5, sd=1)))) var.list <- c("dv1",

Dear R-helpers, I'm using a GLM with poisson errors to model integer count data as a function of one non-integer covariate. The model formula is: log(DV) ~ glm(log(IV,10),family=poisson). I'm getting a warning because the logged DV is no longer an integer. I have three questions: 1) Can I ignore the warning, or is logging the DV (resulting in non-integers) a serious violation of the

In order to experiment with the theora encoder, I bought a mini-DV camcorder a couple of weeks ago; a Panasonic PV-GS9 for $250. I wanted a mini-DV because it is claimed that capturing video from the camcorder to a computer over a firewire cable results in an exact copy of the recorded video. That was not my experience. The video I captured to my computer over the firewire cable, using both

You need to use the script 'llvm-config' to pass correct arguments to g ++: g++ -o broken.o `llvm-config --cxxflags` broken.cpp On Jun 2, 2008, at 9:43 AM, Hendrik Boom wrote: > I took the first two lines of the sample program in the tutorial: > > > hendrik at lovesong:~/dv/lang/hlvm$ cat broken.cpp > #include "llvm/DerivedTypes.h" > #include

Hi all, I summarized actions on http://wiki.centos.org/SpecialInterestGroup/Virtualization/Status tagged with 06/05 The meeting LOG is below Regards Lars lars_kurth How do you want to run this? We have a set of lose ends: the roadmap via http://lists.centos.org/pipermail/centos-virt/2014-April/003763.html <http://lists.centos.org/pipermail/centos-virt/2014-April/003763.html> kbsingh

Taking a look ahead at your QT (OSX version) work, you have Theora Encoding and Decoding on the list. This could be very beneficial as many times the only way to get a constant frame-rate out of QT is to export (and for DV video recorded in QT, this can be a large issue). Another major issue is that the video coming from DV (at least the sources I have used) is almost always

Hola, Por favor, necesito insertar una fila debajo de las filas que tengan DV distinto de cero, pero no me deja insertar hasta el final de la tabla. Esta es mi tabla y este es el código con el que estoy apurado. C ID TIME DV AMT RATE CMT SS II EVID GRUPO VISITA DOSIS VECES FORMA NAP EDAD SEXO ALTURA PESO 11 0 0 3 0 1 1 12 1 3 0 3 2 1 0 77 2 147 74 11 1.417 0.001 0 0 2 0 0 0 3 0 3 2 1 0.001

I'm trying to learn how to do a repeated measures ANOVA in R using lme(). A data set that comes from the book Design and Analysis has the following structure: Measurements (DV) were taken on 8 subjects (SUB) with two experimental levels (GROUP) at four times (TRIAL). In SAS, I use the code: PROC MIXED DATA=[data set below]; CLASS sub group trial; MODEL dv = group trial group*trial;

#I am trying to understand how R fits models for contrasts in a #simple one-way anova. This is an example, I am not stupid enough to want #to simultaneously apply all of these contrasts to real data. With a few #exceptions, the tests that I would compute by hand (or by other software) #will give the same t or F statistics. It is the contrast estimates that R produces #that I can't seem to

Hi, I''m new to puppet so apologises if this is obvious and only proves that I haven''t read the manual from cover to cover (oops, did I really to admit that! ;-) In the DebianRecipies example it uses the variable to determine the relative path to some template files. The variable has been set up at the node level however, there''s the possibility that it hasn''t