similar to: concatenating dataframes (PR#381)

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Sipura has implemented auto-answer in version 0.9.5 of the SPA-841 firmware. However, it is implemented via the Call-Info header, which Asterisk stable doesn't currently support. The attached patch implments a quick hack to support the Call-Info header from the Dial() application by way of setting the CALL_INFO variable. For example, the following macro can be used to dial up a single

Hi R users, I have a time series variable that is only available at a monthly level for 1 years that I need to decompose to a weekly time series level - can anyone recommend a R function that I can use to decompose this series? eg. if month1 = 1200 I would to decompose so that the sum of the weeks for month1 equals 1200, etc.. Many thanks in advance for any help. -- View this message in

Hi, I have a question for my simulation problem: I would like to generate a positive (or semi def positive) covariance matrix, non singular, in wich the spectral decomposition returns me the same values for all dimensions but differs only in eigenvectors. Ex. sigma [,1] [,2] [1,] 5.05 4.95 [2,] 4.95 5.05 > eigen(sigma) $values [1] 10.0 0.1 $vectors [,1]

Hello all, It seems that it is insufficient to rely on MemorySSA to correctly reorder load/stores. For example, we have this following code: v = load q store 10, p => store 10, p v = load q // This is incorrect if p and q may alias In the MemorySSA representation however, there's no syntactic dependency between load/store, because MemorySSA before transformation would look like this:

Dear R community, I've been writing simple functions for the past year and half and have come across a similar problem several times. The execution of a function within my own function produces NaN's or fails to execute as intended. My conundrum is that I can execute the function outside of my function without error, so it's difficult for me, as a novice functioneer, to figure out

Hi, I am trying to cross compile code for ARM Cortex m0, m3, and m4. For m0, I use: -target armv6--eabi -mcpu=cortex-m0 That seems to work. For m3 and m4, I use the following which does not work (fatal error: error in backend: CPU: 'cortex-m3' does not support ARM mode): -target armv7m--eabi -mcpu=cortex-m3 and -target armv7em--eabi -mcpu=cortex-m4 Who can help me with the

m0<-epxression((4*theta1*theta2-theta3^2)/(2*x*theta3^2)-0.5*theta1*x) params<-all.vars(m0) this reads all the params from m0 so theta1,2 and 3 correct? params<-params[-which(params=="x")] checks which params are multiplied by x? np<-length(params) for(i in 1:6){ esp<-get(sprintf("m%d",i-1))

Hi, I'm trying to calculate the value of the variable, dp, below, in the argument to the integral of dnorm(x-dp) * pnorm(x)^(m-1). This corresponds to the estimate of the sensitivity of an observer in an m-alternative forced choice experiment, given the probability of a correct response, Pc, a Gaussian assumption for the noise and no bias. The function that I wrote below gives me an error:

Hello, I am trying to obtain f-values for response (independent) variables from a CCA performed in vegan package, to see which ones of them have significative influence in my dependent variables (like the manual selection in canoco), but I can't find any function (or package) that do such a thing. The dependents variables are species data, and the independents are ambiental data. Than you.

Hi, I am writing a backend and having issues with properly lowering the result of getElementPtr ( specifically the add node that it generates). If we take this IR: %struct.rectangle = type { i24, i24 } ; Function Attrs: nounwind readonly define i24 @area(%struct.rectangle* nocapture readonly %r) #0 { entry: %width = getelementptr inbounds %struct.rectangle* %r, i16 0, i32 0 %0 = load i24*

I'm trying to understand how predicated/masked instructions can be generated in llvm, specifically an instruction where a set bit in the mask will write the new result into the corresponding vector lane in the destination and a clear bit will cause the lane in the destination to remain what it was before the instruction executed. I've seen a few places that suggest 'select' is the

Hi, I've data from an incomplete fatorial design. One level of a factor doesn't has the levels of the other. When I use lm(), the summary() return NA for that non estimable parameters. Ok, I understant it. But I use contrast::contrast(), gmodels::estimable(), multcomp::glht() and all these fail when model has NA estimates. This is becouse vcov() and coef() has different dimensions. Is

Hi Steve, Thanks for the tip regarding MIOperandInfo, I didn't think of that part of the tablegen description. Sadly, I did actually mean: r1 = *(i0 += m0). So increment i0 by m0. Read memory the memory location "pointed" to by i0. Store in r1. Sadly I am not too familiar with compiler terminology, so I don't know if there is a proper term for such a load. On Thu, Oct 23,

Hi, all I want to use LLVM to compile an ARM Cortex-M0 project on windows. Who can send me a sample, including command arguments and introdution about debug process. Thanks a lot. -Steven ***************************** Legal Disclaimer ***************************** "This email may contain confidential and privileged material for the sole use of the intended recipient. Any unauthorized

Dear R-brains, I'm rather new to state-space models and would benefit from the extra confidence in using the excellent package sspir. In a one-factor model, If I am trying to do a simple regression where I assume the intercept is constant and the 'Beta' is changing, how do I do that? How do i Initialize the filter (i.e. what is appropriate to set m0, and C0 for the example below)?

Hello, Is there a built-in test in R for hypothesis testing with samples of known variance? For example, I've got a set of data, a mean to compare against, and a known variance, and I want to determine the p-value for which I can reject the null hypothesis (mu_1 = mu_0) and accept the alternative (mu_1 > mu_0). I've found that JMP and Minitab can both do this (in JMP, it's a

Dear Contributors I have a problem with the collection of data from the results of a test. I need to perform a comparative test over groups of data , recall the value of the pvalue and create a table. My problem is in the way to replicate the analysis over and over again over subsets of data according to a condition. I have this database, called y: gg t1 t2 d 40 1 1

I am having a problem with the package SSPIR. The code below illustrates it. I keep getting the message: "Error in y - f : non-conformable arrays." I tried to tweak the code below in many different ways, for example, substituting rbind for cbind, and sometimes I get a different error message, but I could not find a variation of this code that would work. Any help will be greatly

Hi everyone, this should be pretty basic but I need asking for help as I got stuck. I am running simple linear regression models on R with k regressors where k > 1. In order to automate my code I packed all the regressors in a matrix X so that lm(y~X) will always produce the results I want regardless of the variables in X. I am new to R but I found this advice somewhere so I guess it is