search for: jlaurentum

Hey fellas: I would like to integrate the following function: integrand <- function (x,t) { exp(-2*t)*(2*t)^x/(10*factorial(x)) } with respect to the t variable, from 0 to 10. The variable x here works as a parameter: I would like to integrate the said function for each value of x in 0,1,..,44. I have tried Vectorize to no avail. Thanks in advance, jose romero

Hello list: I am using "cut" and "table" to obtain a frequency table from a numeric sample vector.  The idea is to calculate mean and standard deviation on grouped data.  However, I can't extract the midpoints of the class intervals, which seem to be strings treated as factors.  How do i extract the midpoint? Thanks, jose loreto [[alternative HTML version deleted]]

Hey fellas: In the context of the gambler's ruin problem, the following R code obtains the mean duration of the game, in turns: # total.capital is a constant, an arbitrary positive integer # initial.capital is a constant, an arbitrary positive integer between, and not including # 0 and total.capital # p is the probability of winning 1$ on each turn # 1-p is the probability of loosing 1$ # N

Hello list: Is there an easy way (preferably through one of the standard R packages) of obtaining summary statistics for grouped data? I could split the data into classes by hist, and then progressively calculate all the "columns" i need to obtain the mean and standard deviation, but i was looking for a single function that could do that with a data vector. Thanks in advance, jose

Hello folks: I have a data frame which includes two numeric vectors: "Pa1" and "Ingr" (which represents income).  I run the following code on the R console: ingreso <- factor(ifelse(Ingr<=3000,"bajo","alto")) tapply(Pa1,ingreso,summary) boxplot(Pa1~ingreso) and it works fine.  However, when I "Sweave" through an rnw file containing that

Hola, ¿qué tal? Hace unos meses anuncié en esta lista que había creado un agregador de noticias de R. Este agregador rastrea una serie de blogs, filtra aquellas entradas referentes a R, las agrega y: 1) Crea un RSS, que puede consultarse aquí: http://datanalytics.com/r_blogs_mashup.rss 2) Publica las entradas nuevas en Twitter bajo el usuario @noticiasSobreR. Están todas etiquetadas como

Hello Senne: I am currently teaching a simulation and modeling course in which we use R for most purposes and Sim Py (a python module for discrete event simulation). I am looking for a real-life case such as yours to approach in class- if you wish, i would be happy to look into the case you are describing, along with the data, to work out in the course. If you are interested, please reply with

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Hello list: I have some R code/data sets that i'd like to make available to others through RWeb server use.  The code/data were saved via "save.image" and should be made available by the following command sequence: con <- url("https:// ....") load(con) close(con) However, this is where the problem starts... For one thing, i am using google docs to host the R object

Hello list: I generate by simulation (using different procedures) two sample vectors of size N, each corresponding to a discrete variable and I want to text if these samples can be considered as having the same probability distribution (which is unknown). What is the best test for that? I've read that Kolmogorov-Smirnov and Anderson-Darling tests are restricted to continuous data

Hello list: I am using R through Geany in Ubuntu.  The way i have Geany configured is that upon invoking the exectute command, Geany does a "R <myscript.R >myscript.out", thus getting all input from the myscript.R file and redirecting all output to the myscript.out file. This is a problem when I want to read, say a numeric value, from the keyboard, or when i'd like to output

Hello List: I'm writing in R some code to produce plots for residual analysis and diagnostics in linear regressions.  An example of the plots produced is given for downloading at http://dl.dropbox.com/u/25445316/res_plots.png .  Regarding the example plot, I'd like to point out that: 1) Tendency lines based on lowess estimations are drawn as green continuous curves, 2) "Extra"

Hello list: (This is probably a stupid question).  Is there a "quick and easy" way to confirm the gauss-markov conditions of a linear multiple regression model?  That the mean of the residuals is 0 can easily be tested for. The normality of the residuals as well (shapiro-wilk?).  But what about homoscedasticity? And independence of residuals with respect to the model variables? Thanks

Hello, The following piece of code works fine in R.2.10 (ubuntu): switch(distr,         normal    = {if (is.infinite(param["desv"]))                      n <- c(n,"La desv. estándar no puede ser Inf.")                    if (param["desv"]<0)                      n <- c(n,"La desv. estándar no puede ser <0.")                    },