similar to: how to fit y=m*x

In the capi.conf file, there is a bridge option that allow to "native bridging (CAPI line interconnect) if available", and I found this in the capi-user mailing list : -------------------------------- I suggest you put bridge=yes into each interface. Then, when Asterisk bridges two channels, it looks for the possibility to do a native bridge (call the bridge code of the channel

As this forum proved to be very helpful, I got another question... I'd like to fit data points on which I have an error, dx and dy, on each x and y. What would be the common procedure to fit this data by a linear model taking into account uncertainty on each point? Would weighting each point by 1/sqrt(dx2+dy2) (and taking dx and dy as relative errors) in a lm() fit do the job? I would like to

I have a general question about coefficients estimation of the mixed model. I simulated a very basic model: Y|b=X*\beta+Z*b +\sigma^2* diag(ni); b follows N(0,\psi) #i.e. bivariate normal where b is the latent variable, Z and X are ni*2 design matrices, sigma is the error variance, Y are longitudinal data, i.e. there are ni

Hi R users, I have some data points (Xi, Yi), and they may follow such a pattern Yi = cCOS(Xi) + d, how to find the c and d in R? which function to use? Also, how to get the R2 and p value for this correlation? Thanks for any kind of help. [[alternative HTML version deleted]]

Hi all, I have set up Asterisk and I am able to register with my SIP provider and receive calls. When I try to register with Asterisk from outside I can place calls but tthe other person can't hear me. Have opened port 5060 UDP as well as port 10000 to 20000 UDP. Any ideas? Thanks, Christian

Hey I'm not really sure what I should put on here, but I am having trouble with my R code. I am trying to get the p-values, R^2s etc for a number of different groups of variables that are all in one dataset. This is the code: #Stand counter st<-1 #Collections stands<-numeric(67) slopes<-numeric(67) intercepts<-numeric(67) mses<-numeric(67) rsquares<-numeric(67)

Hi, Optimizes celt_pitch_xcorr for ARM NEON floating point. Changes from RFCv3: - celt_neon_intr.c - removed warnings due to not having constant pointers - Put simpler loop to take care of corner cases. Unrolling using intrinsics was not really mapping well to what was done in celt_pitch_xcorr_arm.s - Makefile.am Removed explicit -O3 optimization - test_unit_mathops.c,

Dear all, I am stuck on the following problem with integrate(). I have been out of luck using RSiteSearch().. My function is g2<-function(b,theta,xi,yi,sigma2){ xi<-cbind(1,xi) eta<-drop(xi%*%theta) num<-exp((eta + rep(b,length(eta)))*yi) den<- 1 + exp(eta + rep(b,length(eta))) result=(num/den)*exp((-b^2)/sigma2)/sqrt(2*pi*sigma2)

Hi, Optimizes celt_pitch_xcorr for floating point. Changes from RFCv2: - Changes recommended by Timothy for celt_neon_intr.c everything except, left the unrolled loop still unrolled - configure.ac - use AC_LINK_IFELSE instead of AC_COMPILE_IFELSE - Moved compile flags into Makefile.am - OPUS_ARM_NEON_INR --> typo --> OPUS_ARM_NEON_INTR Viswanath Puttagunta (1): armv7:

Hi, I am using the uniroot function in order to carry out a bivariate Monte Carlo simulation using the logistics model. I have defined the function as: BV.FV <- function(x,y,a,A) (((x^(-a^-1)+y^(-a^-1))^(a-1))*(y^(a-1/a))*(exp(-((1^(-a^-1)+y^(-a^-1))^a)+y^-1)))-A and the procedure is as follows: Randomly generate values of A~(0,1), y0 = -(lnA)^-1 Where: A=Pr{X<xi|Y=yi-1} and a is the

From: Viswanath Puttagunta <viswanath.puttagunta at linaro.org> Hi, Optimizes celt_pitch_xcorr for floating point. Changes from RFCv1: - Rebased on top of commit aad281878: Fix celt_pitch_xcorr_c signature. which got rid of ugly code around CELT_PITCH_XCORR_IMPL passing of "arch" parameter. - Unified with --enable-intrinsics used by x86 - Modified algorithm to be more

Hi, Optimizes celt_pitch_xcorr for floating point. Changes from RFCv1: - Rebased on top of commit aad281878: Fix celt_pitch_xcorr_c signature. which got rid of ugly code around CELT_PITCH_XCORR_IMPL passing of "arch" parameter. - Unified with --enable-intrinsics used by x86 - Modified algorithm to be more in-line with algorithm in celt_pitch_xcorr_arm.s Viswanath Puttagunta

Dear list, There is, I believe, a minor typo in the example section of influence.measures.Rd. In the final example the word `does` appears where I suspect `dose` is required: I couldn't remember exactly what format patches should be in, so here is one as diff would produce: Index: devel/src/library/stats/man/influence.measures.Rd

Dear users, I am trying to show the equation (including coefficients from the model estimates) for a gam model but do not understand how to. Slide 7 from one of the authors presentations (gam-theory.pdf URL: http://people.bath.ac.uk/sw283/mgcv/) shows a general equation log{E(yi )} = ?+ ?xi + f (zi ) . What I would like to do is put my model coefficients and present the equation used. I am an

Start with the lm() function; i.e., see ?lm -Don -- Don MacQueen Lawrence Livermore National Laboratory 7000 East Ave., L-627 Livermore, CA 94550 925-423-1062 On 6/14/17, 3:40 PM, "R-help on behalf of lily li" <r-help-bounces at r-project.org on behalf of chocold12 at gmail.com> wrote: Hi R users, I have some data points (Xi, Yi), and they may follow such a

Hi, FWIW: /* Taken from R/src/main/unique.c */ static int requal(SEXP x, int i, SEXP y, int j) { if (i < 0 || j < 0) return 0; if (!ISNAN(REAL(x)[i]) && !ISNAN(REAL(y)[j])) return (REAL(x)[i] == REAL(y)[j]); else if (R_IsNA(REAL(x)[i]) && R_IsNA(REAL(y)[j])) return 1; else if (R_IsNaN(REAL(x)[i]) && R_IsNaN(REAL(y)[j])) return 1;

Hi - I have a likelihood function that involves sums of two possions: L = a*dpois(Xi,theta1)*dpois(Yi,theta2)+b*(1-c)*a*dpois(Xi,theta1+theta3)*dpois(Yi,theta2) where a,b,c,theta1,theta2,theta3 are parameters to be estimated. (Xi,Yi) are observations. However, Xi and Yi are usually big (> 20000). This causes dpois to returns 0 depending on values of theta1, theta2 and theta3. My first

Dear All, I am starting to use the tikzDevice package, but I am experiencing some (minor problems). If I try to run the script at the end of the email, I get the following error Error in tools::texi2dvi("normal.tex", pdf = T) : Running 'texi2dvi' on 'normal.tex' failed. Messages: sh: /usr/bin/texi2dvi: not found How do I install the missing texi2dvi? I found some

Dear All, I spent an entire evening in debugging a small, fairly simple program in R - without success. It was my Guru in Bayesian Analysis, Thomas Fridtjof, who was able to diagonose the problem. He said that it took a long time for him also to locate the problem. This program illustrates in some ways the shortcomings of the error messages that R responds with. In this case, it was quite

Dear list, In my previous email, the model I'd like to estimate is rea=a*st+b*mod+error, where a+b=1 and a,b>0. My apologies for the misunderstanding. Thanks for all your help, Jorge On Wed, Jul 23, 2008 at 3:35 PM, Jorge Ivan Velez <jorgeivanvelez@gmail.com> wrote: > > Dear list, > > I have a data set which looks like myDF (see below) and I'd like to >