similar to: Different x-axis scales using c() in latticeExtra

Hi, I use a mboost model to predict my dependent variable on new data. I get the following warning message: In bs(mf[[i]], knots = args$knots[[i]]$knots, degree = args$degree, : some 'x' values beyond boundary knots may cause ill-conditioned bases The new predicted values are partly negative although the variable in the training data ranges from 3 to 8 on a numeric scale. In order to

I was unsure of what suitable goodness-of-fit tests existed in R for logistic regression. After searching the R-help archive I found that using the Design models and resid, could be used to calculate this as follows: d <- datadist(mydataframe) options(datadist = 'd') fit <- lrm(response ~ predictor1 + predictor2..., data=mydataframe, x =T, y=T) resid(fit, 'gof'). I set up a

Hi Group, Create some example data. set.seed(1) wide_data <- data.frame( id=c(1:10), predictor1 = sample(c("a","b"),10,replace=TRUE), predictor2 = sample(c("a","b"),10,replace=TRUE), predictor3 = sample(c("a","b"),10,replace=TRUE), measurement1=rnorm(10), measurement2=rnorm(10)) head(wide_data) id

R-help: I am trying to decide between using a multiple linear regression or a linear mixed effects model for my data: model1 <- lm (responsevariable ~ predictor1 + predictor2 + predictor3 + predictor4, data= data) model2 <- lme (responsevariable ~ predictor1 + predictor2 + predictor3 + predictor4, random = ~1 | site, data= data) anova (model1, model2) but I keep getting the

Dear all, I got a couple of warnings using panel.levelplot.raster, In panel.levelplot.raster(..., interpolate = TRUE) : 'y' values are not equispaced; output will be wrong although I was quite sure my data were equally spaced (indeed, I created them with seq()). A closer look at the source code reveals that the function tests for exact uniformity in grid spacing, if

Hello, I came across a problem when building a randomForest model. Maybe someone can help me. I have a training- and a testdataset with a discrete response and ten predictors (numeric and factor variables). The two datasets are similar in terms of number of predictor, name of variables and datatype of variables (factor, numeric) except that only one predictor has got 20 levels in the training

Estimada comunidad, estoy haciendo un grafico con la funcion xYplot (paquete Hmisc) para agregar barras de error a los puntos del grafico. Pero pasa algo que no me gusta: aparece el nombre de las series en el grafico. Alguien sabe como puedo eliminarlas ? no quiero usar ggplot porque ya tengo hechos todos los graficos con lattice. Aqui el codigo que uso y los datos (estan separados por tab, no

Dear R users, I want to plot a one variable continuous function f(x) vs x, x=[0,1]. Say for example: f(x)= x^2. Now, using the command plot(f~x) I will get a curve where the range of x-axis is [0,1] with all equispaced label. But, I need something else, and that is: my curve will be such that 80% on x-axis the range would be [0,0.5] and the rest 20% would contain [0.5,1]. Let me draw informally

"vector[s]" should be plural in line 54 ... cheers Ben Bolker ---- Index: ts.Rd =================================================================== --- ts.Rd (revision 75540) +++ ts.Rd (working copy) @@ -54,7 +54,7 @@ } \details{ The function \code{ts} is used to create time-series objects. These - are vector or matrices with class of \code{"ts"} (and additional

I have an irregular time series in a Zoo object, and I've been unable to find any way to do an FFT on it. More precisely, I'd like to do an NFFT (non-equispaced / non-uniform time FFT) on the data. The data is timestamped samples from a cheap self-logging accelerometer. The data is weakly regular, with the following characteristics: - short gaps every ~20ms - large gaps every ~200ms

Estimados, tengo el siguiente problema: Tengo que graficar la concentracion de un metabolito en algunas muestras contra la concentracion del solvente con que fue extraido. Las concentraciones varian desde cero (para un control) hasta varios miles de unidades de concentracion (miliMolar). Para que se puedan diferenciar los puntos en el eje X, se ha usado una escala logaritmica. Hasta ahi todo

I have some time stamped events that are supposed to be unrelated. I have plotted them and that assumption does not appear to be valid. http://metrak.com/tmp/sevents.png is a plot showing three sets of events over time. For the purpose of this exercise, the Y value is irrelevant. The series are not sampled at the same time and are not equispaced (just events in a log file). The plot is

Dear users, I am trying to export polygons from Arcmap into Spatstat to run some simulations using functions available in Spatstat package. One particular area to be exported is formed by a number of polygons defining the external boundaries of the area (as a groups of islands) and a number of polygons inside the previous ones, as ?holes? not to be considered as part of the area. I have

R experts - I'm using John Fox's sem package to analyze a simple path model (two correlated predictor variables directly influencing a single criterion variable): Predictor1 -> Criterion Predictor2 -> Criterion Predictor1 <-> Predictor2 I'm giving a presentation on this material next week, and I'd like to use component-residual plots (i.e., partial residual plots)

Hi all, in my search for a nice binary2decimal method, I received this nice code (thanx to Uwe Ligges): bindec <- function(b) sum(as.integer(unlist(strsplit(b, ""))) * 2^(floor(log10(b)):0)) It fails, however, with: > bindec(1000) [1] 4 Warning message: longer object length is not a multiple of shorter object length in: as.integer(unlist(strsplit(b, "")))

Dear R users: Sorry for this simple question: I am writing a function where I would need to pickup p values and make -log10 of it. The p values are from an anova output and sometime it can yield me 0. -log10 (0) [1] Inf I can not replace Inf with 0, which not case here. This is restricting me to go further in the function and out me the error. You help is highly appreciated. Thanks; --

Dear all, I did a non-linear least square model fit y ~ a * x^b (a) > nls(y ~ a * x^b, start=list(a=1,b=1)) to obtain the coefficients a & b. I did the same with the linearized formula, including a linear model log(y) ~ log(a) + b * log(x) (b) > nls(log10(y) ~ log10(a) + b*log10(x), start=list(a=1,b=1)) (c) > lm(log10(y) ~ log10(x)) I expected coefficient b to be identical

Dear S-PLUS/R users: Do you know any default function or a user contributed function that can draw an ellipse with given axes and origin? Thanks for any help. Paul. -- Romance, like alcohol, should be enjoyed, but should not be allowed to become necessary. -- Edgar Friedenberg -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list --

Hello. My name is Akashah. i work at metabolic laboratory. From my study, i found that volcano plot can help a lot in my section.  i already studied about the volcano plot and get the coding to run in R software, unfortunately, there is may be something wrong with the coding. This is because  no graph appear, but no error (blue color text) was shown on the R console. Below is the coding for

Hi, I am trying to use CART to find an ideal cut-off value for a simple diagnostic test (ie when the test score is above x, diagnose the condition). When I put in the model fit=rpart(outcome ~ predictor1(TB144), method="class", data=data8) sometimes it gives me a tree with multiple nodes for the same predictor (see below for example of tree with 1 or multiple nodes). Is there a way