similar to: Create a time-series from cross-sectional data that has each year as a separate column

Hello all, I'm struck with a very strange problem today. I've an AGI with some code subroutine snippet as follows: sub enable_sbc($) { my $carrier = shift; my $tmp = substr($carrier,1); my $jkh = $tmp; $server_port = $ast_agi->get_variable("SIPPEER($jkh,port)"); $ser_ip = $ast_agi->get_variable("SIPPEER($tmp,ip)");

Hi, I am trying to do a multiple regression on the dataset "Hdma", available in the Ecdat package. The data looks like this: > str(Hdma) 'data.frame': 2381 obs. of 13 variables: $ dir : num 0.221 0.265 0.372 0.32 0.36 ... $ hir : num 0.221 0.265 0.248 0.25 0.35 ... $ lvr : num 0.8 0.922 0.92 0.86 0.6 ... $ ccs : num 5 2 1 1 1 1 1 2 2 2

We have 1 queue called helpdesk and are setting up a second one called isp. The helpdesk queue is for internal support calls and isp for our ISP customer calls. Both of these queues will be directed to the same agents (helpdesk phone extensions). We want to have the separate queues for tracking purposes but the queued calls need to be ordered and answered as if there was only one queue. For

I'm working on a Java implementation of portions of LLVM and have a question about licensing. The project won't contain any LLVM source code although I can foresee using JNI stubs that link against LLVM libraries. It does however in many cases follow LLVM APIs. From my understanding of the University of Illinois/NCSA license this means: 1. I need to include the copyright notice

Hi, I am trying to write dial plan for sip to auto answer (auto attend) the incoming call to the sip phone. - If i call from sip1 to sip2 then sip2 should automatically answer the call and play some sound file. I am trying to do this but as new to the asterisk dial plan configuration , so not able Todo this. help me if anyone already done this setup. Regards Upendra. -------------- next part

Dear R saviors, kindly address to this problem, I would really appreciate any takers. I am trying to resolve this issue of IMR in clustered (multilevel) cross-sectional panel data for more than two months now,. The characteristics of my dataset are as follows: - some 900 000 individuals - total of 60 countries - cross-sectional time series at the country level max 10 years, not all

Hi all, Is there a package in R to perform time series cross-sectional regression analysis (like the TSCSREG procedure in SAS)? Thanks for the info. Thanks and Regards, Shubha Karanth | Amba Research Ph +91 80 3980 8283 | Mob +91 94 4886 4510 Bangalore * Colombo * London * New York * San José * Singapore * www.ambaresearch.com This e-mail may contain confidential and/or

Dear all, I'd appreciate some advice on the following problem. I'm attempting to analyse a nested cross-sectional design in which an intervention was offered to a series of randomly selected (small) communities, so the unit of randomisation is the community. All available individuals in each community were interviewed before the intervention and again at follow-up

Howdy What I 'd like to analyze with a large data on building permits is to find time series effect of urban policy on buildings as well as cross-sectional effects in any. In 1990 the specialZone urban policy was introduced. I guess that the effects of this specialZone policy would be different from countys. There are counties that do not welcome this specialZone forced to design it. One of

Hi all, I'm trying to run an AGI in PERL which uses the module DBD-Oracle. Currently my AGI is working fine in my two servers but not in my other four servers. When I tried execute an AGI (as a user asterisk) in command line it works fine (even I also declare environmental variables in user profile and in my AGI), but when I tried to call my AGI (perl) in dial plan, it don't get

I'm wondering if any other Asterisk users have a recommendation for a reliable SIP Trunk provider that supports Asterisk and offers decent support. I've worked with Coredial, Broadvox, and Broadvoice and have had some bad experiences with each of these providers. Broadvoice offers low cost service, however I have constant issues with Broadvoice blocking my customers due to Asterisk

Hello, I have a RAID5 array on my CentOS 5.6 x86_64 workstation which "suddenly" failed to work (actually after the system could not resume from a suspend). I had recently issues after moving the workstation to another office, where one of the disks got accidently unplugged. But the RAID was working and it had reconstructed (as far as I can tell) the data. After I replugged the disk,

Greetings, I have generated several ROC curves and would like to compare the AUCs. The data are cross sectional and the outcomes are binary. I am testing which of several models provide the best discrimination. Would it be most appropriate to report AUC with 95% CI's? I have been looking in to the "net reclassification improvement" (see below for reference) but thus far I can only

I can't figure out why this function wont work. #Custom Function used fallInBand <- function(x){ #Assume the bands fall go up form 0 to 100 in intervals of 5 then from 100 to 1000 in intervals of 100. #returns the location (band number) if (is.na(x) == FALSE) { if(x < 100) {#bands of 5 if((x %% 5) >=0){#falls within the band Result = as.integer(x/5)+1

Hello again Max. A correction to my response from yesterday. Things were better than they seemed. I thought it over, checked Arellano's panel book and Driscoll and Kraay (Rev. Econ. Stud. 1998) and finally realized that vcovSCC does what you want: in fact, despite being born primarily for dealing with cross-sectional correlation, 'SCC' standard errors are robust to "both

Hi, I would like to achieve the following with my dovecot server: - listen von FQDN 'mail.foo.example.com'/IP 'A' for imaps and pop3s with an SSL certificate for 'mail.foo.example.com' - listen von FQDN 'mail.bar.example.com'/IP 'B' for imaps and pop3s with an SSL certificate for 'mail.bar.example.com' I stumbled over a posting by Timo made

Hi, I'm looking for ideas or packages with relevant algorithms for calculating the connectivity across a grid, where connectivity is defined as the minimum amount of cross-sectional area along a continuous path. The upper boundary of the cross-sectional area is a fixed elevation, and the lower boundary is a gridded surface of variable elevation. My variable elevation surface represents the

`grDevices::convertColor` performance can be improved by 30-300x with small changes to the code. `colorRamp(space='Lab')` uses `convertColor` so it too benefits from substantial performance gains. `convertColor` vectorizes explicitly over the rows of the input color matrix using `apply`. The level-1 patch [1] illustrates a possible minimal set of changes to achieve this with just R

Dear Developers, Having spent time developing and thinking about how data aggregation and summary statistics can be enhanced in R, I would like to present my ideas/efforts in the form of two commands: The first, which for now I called 'collap', is an upgrade of aggregate that accommodates and extends the functionality of aggregate in various respects, most importantly to work with

Dear All, I am working with skewed-t copula in my research recently, so I needed to write an mle procedure instead of using a standard fit one; I stick to the sn package. On subsamples of the entire population that I deal with, everything is fine. However, on the total sample (difference in cross-sectional dimension: 30 vs 240) things go wrong - the objective function diverges to infinity. I