Re: [R] anova.coxph with subsets of data

Ka Shing Centre, Robinson Way. Cambridge CB2 0RE England From: Therneau, Terry M., Ph.D. [thern...@mayo.edu] Sent: Wednesday, January 29, 2014 2:35 PM To: Oscar Rueda; r-help@r-project.org Subject: Re: [R] anova.coxph with subsets of data --- begin

Re: [R] anova.coxph with subsets of data

cs. University of Cambridge. Cancer Research UK Cambridge Institute. Li Ka Shing Centre, Robinson Way. Cambridge CB2 0RE England From: David Winsemius [dwinsem...@comcast.net] Sent: Wednesday, January 29, 2014 12:10 AM To: Oscar Rueda Cc: r-help@r-proj

[R] anova.coxph with subsets of data

Dear list, I'm using the rms package to fit some Cox models. I run anova() on them to obtain sequential p-values, but I'm getting strange results when I run it on a subset of the data. Following the example on the help page of anova.coxph: > library(rms) > data(ovarian) > fit <- coxph(Surv(fut

[R] Positive Smoothing in fda package

Dear all, I'm trying to build some fda objects using smooth.pos() from fda package. Here is what I try: >X <-c(0.4541139, 0.4802537, 0.5091228, 0.3894931, 2.1512258, >7.9301281, 62.3876109, 54.1168247, 67.8769904, 91.0670615, 20.0682440) >basis <- create.bspline.basis(c(-100, 100), 7, 5) >MDA

Re: [R] 回复： Bayesian Hidden Markov Models

; Normal-3 0.037727330 0.218834862 0.333794793 0.004936521 0.374412381 > Gain 0.053064705 0.189481114 0.233947328 0.068592117 0.212423356 > Gain > Loss-1 0.101572465 > Loss-2 0.077932083 > Normal-1 0.041455335 > Normal-2 0.002855048 > Normal-3 0.03029

Re: [R] Bayesian Hidden Markov Models

),2,2) > Q.NH(beta=tran, x=1) > [,1] [,2] > [1,] 0.5 0.5 > [2,] 0.5 0.5 > > Many thanks for your further help and time. > > James Allan > > --- 12年2月28日，周二, Oscar Rueda [via R] > 写道： > > > 发件人: Oscar Rueda [via R] > 主题: Re: Bayesian Hid

Re: [R] Bayesian Hidden Markov Models

rst-order > homogeneous Markov chain, i.e. the transition matrix is constant. > > So, Could you please tell me how can I adjust the R functions in your package > to implement my analysis? > > Best Regards, > > James Allan > > > --- 12年2月27日，周一, Oscar Rueda [vi

Re: [R] Bayesian Hidden Markov Models

Dear James, Although designed for the analysis of copy number CGH microarrays, RJaCGH uses a Bayesian HMM model. Cheers, Oscar On 27/2/12 08:32, "monkeylan" wrote: > Dear R buddies, > > Recently, I attempt to model the US/RMB Exchange rate log-return time series > with a *Hidden Markov mode

[R] Warning in ansari.test

Dear list, When I try to run the Ansari-Bradley test on two long vectors I obtain a warning and the p-value is NA: > set.seed(12) > x <- rnorm(10) > y <- rnorm(10) > ansari.test(x,y) Ansari-Bradley test data: x and y AB = 5002890779, p-value = NA alternative hypothesis: true

Re: [R] RJMCMC.

Dear Marcus, As others have pointed out, RJaCGH uses Reversible Jump MCMC to fit a non-homogeneous Hidden Markov Model to array CGH data, but it can be used for other applications too. It can be easily adapted to homogeneous HMMs and even to mixed models. It also contains implementations of add

Re: [R] t-test problem

Hi Worik, You can try 2*pt(abs(t1$statistic), t1$parameter, lower.tail=FALSE) If the test is two sided. Cheers, Oscar Oscar M. Rueda, PhD Postdoc, Breast Cancer Functional Genomics Cancer Research UK Cambridge Research Institute Li Ka Shing Centre Robinson Way Cambridge CB2 0RE England O