similar to: gam function & time trend splines

Dear R users - I have a list of patient identifiers and diagnoses from inpatient admissions. I would like to reorganize the list, presently in a long format to a wide format in reshape, but in the absence of a "time" element, I am uncertain how to do this - any help greatly appreciated. ID Dx A nausea A diabetes A kidney failure A heart attack A fever B fever B

Hello everyone, I wanted to ask if there is an R-package to fit the following Poisson regression model log(\lambda_{ijk}) = \phi_{i} + \alpha_{j} + \beta_{k} i=1,\cdots,N (subjects) j=0,1 (two levels) k=0,1 (two levels) treating the \phi_{i} as nuinsance parameters. Thank you very much -- -Tony [[alternative HTML version deleted]]

Hi, This probably seems somewhat reaching since CrossOver isn't Wine, but well, it's built on Wine, so I thought I might just answer here anyway. I'm running WoW through Innerspace, which causes some weird problems. With Innerspace loaded together with WoW it'll act as alt + shift is being held down. Innerspace has an alias binded to alt + shift + t which will make WoW go into

Dear list users How is it possible to visualise both a linear trend line and a quadratic trend line on a plot of two variables? Here my almost working exsample. data(Duncan) attach(Duncan) plot(prestige ~ income) abline(lm(prestige ~ income), col=2, lwd=2) Now I would like to add yet another trend line, but this time a quadratic one. So I have two trend lines. One linear trend line

I have a 3d scatter plot and I need to add a trend line. I can add a regression plane, but I need a line, not a plane. Thanks. -- View this message in context: http://n4.nabble.com/3d-trend-line-tp1053686p1053686.html Sent from the R help mailing list archive at Nabble.com.

Hi everyone, I'm trying to determine the significance of a trendline. From my internet search months ago, I came across the following post. I modified tim and dat for simiplicity. tim <- 1:10 dat <- c(0.17, 1.09 ,0.11, 0.82, 0.23, 0.38 ,2.47 ,0.41 ,0.75, 1.44) fstat <- summary(lm(dat~tim))$fstatistic p.val <-

Dear All, My question is: how can I estimate VECM system with "unrestricted trend" (aka "case 5") option as a deterministic term? As far as I know, ca.jo in urca package allows for "restricted trend" only [vecm <- ca.jo(data, type = "trace"/"eigen", ecdet = "trend", K = n, spec = "transitory"/"longrun")].

hej! can anyone help me with a hint how to find a function to fit a linear trend line into a scatter plot. as well as testing it for significance. thanx/thisse

Hi! I am searching for the Cochran-Armitage-trend-test. Is it included in an R-package? Thank you! --

Hi R Users, I wish to estimate if there is a trend in my relative risk obtained by coxph. The best i've found is a method from Greenland and Longnecker ( Am J Epidemiology 1992 vol 135 (11) - p 1301-9 ). But all I have is my relative risk and their std error. Is there a command in R that can do this ? If there is someone with a better method ? Thanking you in advance, I look forward your

To the R-help list, In the documentation of the prop.trend.test function in the stats package, no bibliography has been provided which would allow one to find out the theoretical basis of that function and/or details of its implementation. May I suggest that some bibliography be included, as it generally happens with other statistical functions. I currently use R 2.8.0 running on Windows XP.

Hello, I used glsm.mcmc and likfit.glsm to create model. Now I want to predict at different locations, but I can't get glsm.krige to work. I keep getting the error that trend.d and trend.l must have similar specifications. I have tried numerous ways to include the covariates in the glsm.krige model, and I keep getting the same error message. The bolded part is the part that doesn't work.

Hi R-help, I'd like to extract the seasonal component of a short timeseries, and was hoping to use stats::decompose. I don't want to decompose the 'trend' component so I thought I should call decompose(x,filter=0). I think I've either misunderstood the filter argument or come upon a bug/feature in decompose. # EXAMPLE

I partly answered my question since independence_test() function in coin package apparently do Cochran-Armitage trend test just like Eric Lecoutre's function tabletrend() - slightly modified here: > independence_test(pheno ~ geno, data = dat2, teststat = "quad", scores = list(geno = c(0, 1, 2))) Asymptotic General Independence Test data: pheno by groups 1 < 2

Hi, I have a time series (say "x") of 13 years showing an evident increase. I want to exclude two observations (the fourth and 10th), so I do: > trend.test(x[-c(4,10)]) where: > x[-c(4,10)] [1] 7 37 79 72 197 385 636 705 700 1500 1900 and I get: Spearman's rank correlation rho data: x[-c(4, 10)] and time(x[-c(4, 10)]) S = 4, p-value < 2.2e-16

Hello! I am applying the ADF.test function from package uroot to a time series of data. When I apply the full test, incorporating drift and trend terms, the regressor estimate of the drift term is not significantly different from zero. So I apply the test to a model without drift term, with deterministic trend only. But then I always get the following error:

Hi All, I am a newcomer to R. Could anyone explain me how to define link functions for either mu/sigma to allow for quadratic trends in the same, when fitting non-stationary GEV distributions? Thanks -- View this message in context: http://www.nabble.com/QUADRATIC-TREND-FOR-LINK-FUNCTIONS-ON-NON-STATIONARY-GEV-tp23360751p23360751.html Sent from the R help mailing list archive at Nabble.com.

Hi (again), Please find here a correction of the function I send previously --------------------------------------------------------- tableChisqMH=function(x) { n=sum(x) G2=(n-1)*(tablepearson(x)$estimate^2) dll=1 p.value=1-pchisq(G2,dll) out=list(estimate=G2,dll=dll,p.value=p.value,dim=dim(x),name="Mantel-Haenszel Chi-square") return(out) }

I have a mortality data over many years and I wish to plot the data and also add some smoother to clearly highlight the trend. How could I do that in R with base graphics or ggplot? I have the following sample data: require(lubridate) mdate<-seq(ymd('2000-01-01'),ymd('2010-12-31'), by = '1 day') death<- rnorm(4018, 80, 45) df<-cbind(mdate,death)

Hello, I have a netcdf file for summer monsoon rainfall gridded data over Indian region. How can I find the linear trend in R? regards Sourabh Bal Dr. Sourabh Bal Assistant Professor Department of Physics Swami Vivekananda Institute of Science and Technology Kolkata 700145 [[alternative HTML version deleted]]