Wild guess: You have huge and high dimensional VAR models, i.e. the
matrices get huge and you use huge amounts of memory and you use more
than what is available physically. The operating system protects itself
by killing processes in such a case...
Best,
Uwe Ligges
On 31.05.2016 20:29, Vivek Singh wrote:
Hi,
I am using VARS (vector autoregressive model). The process gets killed
after running for sometime. Following is the output of R.
vivek@isds-research:~/cloudAuction/padding/panel$ cat var.Rout
R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
Natural language support but running in an English locale
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
[Previously saved workspace restored]
data=read.csv("output1.csv")
attach(data)
only_variables= subset(data, select=c(-date,-hour,-minute,-sec))
library("vars")
Loading required package: MASS
Loading required package: strucchange
Loading required package: zoo
Attaching package: ‘zoo’
The following objects are masked from ‘package:base’:
as.Date, as.Date.numeric
Loading required package: sandwich
Loading required package: urca
Loading required package: lmtest
summary(VAR(only_variables, p = 1, type ="both"))
*Killed*
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