tsDyn
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MatthieuStigler
TVECM does not work with two threshold values
Hi, Matthieu
Recently I am trying to use TVECM in my paper. When I write "nthresh=2" in Rstudio, an error happens and it is listed below.
library(tsDyn) #> Registered S3 method overwritten by 'quantmod' #> method from #> as.zoo.data.frame zoo packageVersion("tsDyn") #> [1]11.0.2 price<-read_excel("E:/spot and futures price.xlsx") tvec<-TVECM(price,nthresh=2,lag=2,ngridBeta=300,ngridTh=300,plot=TRUE,trim=0.05,common="All") #> error in allgammas[seq(from=wh.thresh + ninter, to=length(allgammas) - :only 0's may be mixed with negative subscripts
However, R runs smoothly if nthresh is set to 1. Could you please fix the bug?
Best Xi
Sorry, your code is not reproducible. See How to make a great R reproducible example
Here is a minimal reproducible code using reprex(), where the code works fine:
library(tsDyn)
#> Registered S3 method overwritten by 'quantmod':
#> method from
#> as.zoo.data.frame zoo
out <- TVECM(zeroyld,nthresh=2,lag=2,ngridBeta=300,ngridTh=300,plot=TRUE,trim=0.05,common="All")
#> 1233 (1.4%) points of the grid lead to regimes with percentage of observations < trim and were not computed
#> Best threshold from first search -1.312
#> Best cointegrating value 1.045747
#> There were 3 thresholds values which minimize the SSR in the conditional step, the first one was taken
#> Second best (conditionnal on the first one) -1.312 -0.529 SSR 150.3263
#> There were 12 thresholds values which minimize the SSR in the iterative step, the first one was taken
#> Second step best thresholds -1.414 -0.529 SSR 149.0925
Created on 2022-05-27 by the reprex package (v2.0.1)
library(tsDyn)
#> Registered S3 method overwritten by 'quantmod':
#> method from
#> as.zoo.data.frame zoo
packageVersion("tsDyn")
#> [1] '11.0.2'
price <- structure(list(`futures price` = c(6.4, 6.23, 6.17,
6.49, 6.3, 6.05, 5.89, 5.75, 5.74, 5.91, 5.5, 5.47, 4.98,
4.83, 5.32, 4.53, 4.23, 4.01, 4.08, 3.89, 3.7, 3.33, 4.23,
4.21, 4.3, 4.07, 4.09, 4.44, 4.37, 4.47, 5.11, 5.13, 5.07,
4.99, 4.57, 4.86, 5.18, 5.07, 4.47, 4.2, 4.37, 4.8, 4.57,
4.53, 4.14, 4.19, 4.24, 4.18, 3.88, 3.66, 3.45, 3.63, 3.71,
3.48, 3.47, 3.93, 4.38, 4.11, 4.44, 4.57, 4.9, 4.76, 4.9,
4.87, 4.99, 5.13, 5.14, 4.73, 4.25, 4.29, 4.71, 4.7, 3.05,
2.72, 3.04, 3.13, 2.85, 3.05, 2.98, 2.92, 3.06, 3.27, 3.08,
3.04, 3.73, 3.86, 3.69, 3.33, 3.22, 3.47, 3.65, 3.49, 3.51,
3.36, 3.51, 3.45, 3.6, 3.77, 3.91, 3.87, 3.91, 3.95, 4.07,
4, 4.16, 4.38, 4.74, 4.55, 4.67, 4.4, 4.35, 4.09, 4.27, 4.42,
4.2, 4.23, 4.28, 4.54, 4.28, 4.23, 4.16, 4.08, 4.03, 4.04,
4.12, 4.12, 4.18, 4.2, 4.25, 4.29, 4.32, 4.32, 4.27, 4.33,
4.38, 4.41, 4.5, 4.51, 4.44, 4.31, 4.29, 4.35, 4.32, 4.34,
4.51, 4.42, 4.53, 4.58, 4.55, 4.49, 4.4, 4.95, 5.32, 5.3,
5.12, 5.61, 5.39, 5.46, 5.66, 5.35, 5.35, 5.41, 5.37, 5.46,
5.39, 5.02, 5.15, 5.11, 4.97, 4.87, 4.77, 4.62, 4.82, 4.96,
5.18, 5.13, 4.59, 4.71, 4.67, 5.01, 4.83, 5.09, 4.81, 4.62,
4.56, 4.8, 4.8, 4.49, 4.61, 4.65, 4.59, 4.5, 4.35, 4.42,
4.41, 4.43, 4.4, 4.49, 4.43, 4.36, 4.5, 4.48, 4.64, 4.79,
4.9, 5.02, 4.9, 4.8, 4.67, 4.91, 4.69, 4.58, 4.51, 4.53,
4.63, 4.83, 5.07, 5.07, 4.93, 5.04, 5.03, 5.26, 5.37, 5.52,
5.71, 5.52, 5.84, 5.82, 6.07, 6.44, 6.42, 6.4, 6.24, 6.38,
6.58, 6.8, 6.74, 6.98, 7.13, 7, 6.21, 6.5, 7.06, 6.61, 6.81,
6.77, 6.8, 6.9, 6.89, 6.82, 6.43, 6.29, 5.87, 5.75, 6.01,
6.18, 5.86, 5.85, 5.17, 4.34, 4.64, 5.06, 4.87, 4.7, 4.99,
4.87, 5.13, 5.33, 5.25, 5.55, 5.56, 5.69, 5.73, 5.08, 5.22,
5.43, 5.2, 5.23, 5.24, 5.15, 5.25, 5.31, 5.3, 4.78, 4.8,
4.7, 4.84, 5.16, 5.12, 5.09, 5.17, 5.05, 5.14, 5.43, 5.54,
5.44, 5.49, 5.55, 5.66, 5.63, 5.7, 5.54, 5.65, 5.79, 5.74,
5.7, 5.76, 5.81, 6.03, 6.01, 5.67, 5.56, 5.75, 5.68, 5.74,
5.88, 5.94, 6.15, 6, 6.06, 6.17, 6.05, 6.13, 6.19, 6.03,
6.21, 6.27, 6.23, 6.2, 5.94, 5.97, 6.13, 6.11, 6.23, 6.38,
6.34, 6.43, 6.34, 6.35, 6.32, 6.29, 6.43, 6.38, 6.39, 6.38,
6.11, 6.26, 6.27, 6.12, 6.1, 6.04, 5.91, 5.79, 5.97, 6.01,
5.98, 5.65, 5.8, 5.91, 5.75, 5.84, 5.69, 5.73, 6.12, 6.04,
6.06, 6.08, 6.21, 6.13, 6.14, 6.18, 6.34, 6.41, 6.29, 6.16,
6.42, 6.35, 6.58, 6.49, 6.63, 6.76, 6.72, 6.8, 6.79, 6.62,
6.9, 7.02, 6.96, 7, 7.05, 7.12, 7.09, 7.04, 7.07, 6.85, 6.84,
6.66, 6.66, 6.74, 6.74, 6.66, 6.89, 6.93, 6.84, 6.74, 6.74,
7.32, 7.15, 7.16, 7.24, 7.19, 6.78, 6.82, 6.87, 6.85, 6.96,
7.07, 7.09, 7.14, 7.07, 7.01, 6.96, 6.93, 7.12, 7.41, 7.65,
7.66, 7.48, 7.35, 7.33, 7.71, 7.47, 7.06, 7.1, 6.95, 6.73,
6.75, 6.8, 6.68, 6.82, 6.41, 6.46, 6.49, 6.73, 6.67, 7.04,
7.04, 7.05, 6.99, 6.97, 6.78, 6.9, 6.94, 7.17, 7.13, 7.03,
6.96, 6.81, 6.81, 6.88, 6.85, 7.14, 7.09, 7.27, 7.3, 7.17,
7.36, 7.4, 7.56, 7.44, 7.54, 7.63, 7.6, 7.59, 7.6, 7.37,
7.35, 7.3, 7.3, 7.22, 7.18, 7.32, 7.24, 7.44, 7.4, 7.44,
7.56, 7.5, 7.61, 7.51, 7.41, 7.45, 7.41, 7.46, 7.48, 7.58,
7.52, 7.33, 7.44, 7.44), `spot price` = c(6.47, 6.18, 6.18,
6.46, 6.27, 6.05, 5.89, 5.73, 5.55, 5.88, 5.46, 5.4, 4.94,
4.8, 5.25, 4.55, 4.25, 4.01, 4.06, 3.88, 3.7, 3.37, 4.16,
4.49, 4.35, 4.06, 4.1, 4.42, 4.37, 4.49, 5.11, 5.15, 5.07,
5.02, 4.58, 4.86, 5.2, 5.07, 4.45, 4.2, 4.36, 4.79, 4.57,
4.53, 4.12, 4.17, 4.22, 4.18, 3.88, 3.65, 3.46, 3.65, 3.71,
3.49, 3.44, 3.9, 4.4, 4.1, 4.43, 4.56, 4.89, 4.82, 4.87,
4.85, 4.95, 5.11, 5.13, 4.73, 4.29, 4.26, 4.67, 4.72, 3.02,
2.68, 2.99, 3.02, 2.83, 3.02, 2.95, 2.92, 3.06, 3.25, 3.08,
3.04, 2.95, 3.65, 3.68, 3.52, 3.23, 3.23, 3.47, 3.55, 3.49,
3.2, 3.3, 3.41, 3.5, 3.65, 3.96, 3.8, 3.9, 3.9, 4.12, 4.14,
3.97, 4.55, 4.4, 4.65, 4.63, 4.3, 4.33, 4.19, 4.04, 4.31,
4.31, 4.06, 4.23, 4.55, 4.4, 4.16, 4.2, 4.06, 3.95, 3.99,
4.11, 4.1, 4.06, 4.1, 4.26, 4.3, 4.28, 4.24, 4.33, 4.36,
4.3, 4.4, 4.39, 4.43, 4.48, 4.4, 4.28, 4.33, 4.31, 4.28,
4.43, 4.49, 4.44, 4.57, 4.54, 4.49, 4.38, 4.75, 5.05, 5.38,
5.13, 5.3, 5.37, 5.42, 5.44, 5.4, 5.3, 5.37, 5.47, 5.33,
5.38, 5.15, 5.05, 5.12, 5.05, 4.88, 4.7, 4.58, 4.56, 5.07,
5.27, 5.14, 4.78, 4.64, 4.58, 4.61, 4.81, 4.78, 4.87, 4.63,
4.64, 4.7, 4.73, 4.78, 4.47, 4.57, 4.63, 4.46, 4.33, 4.44,
4.44, 4.48, 4.38, 4.41, 4.41, 4.36, 4.36, 4.47, 4.49, 4.7,
4.65, 4.8, 4.77, 4.84, 4.69, 4.7, 4.65, 4.69, 4.56, 4.45,
4.52, 4.73, 5.01, 5.04, 5.05, 4.93, 5.02, 4.97, 5.34, 5.47,
5.55, 5.6, 5.48, 5.93, 5.97, 6.01, 6.45, 6.34, 6.3, 6.21,
6.31, 6.7, 6.74, 6.92, 6.85, 7.1, 6.85, 6.47, 6.83, 6.97,
6.65, 6.89, 6.71, 6.72, 6.93, 6.81, 6.51, 6.19, 6.15, 6,
6, 6.1, 6.08, 5.8, 5.35, 5.1, 4.17, 4.9, 4.6, 4.75, 4.72,
5.03, 5, 5.26, 5.3, 5.23, 5.46, 5.62, 5.77, 5.52, 5.21, 5.39,
5.28, 5.03, 5.25, 5.09, 5.1, 5.28, 5.34, 4.75, 4.72, 4.6,
4.59, 5.23, 5.08, 4.98, 5.05, 5.1, 4.94, 5.19, 5.5, 5.41,
5.45, 5.4, 5.63, 5.68, 5.55, 5.6, 5.56, 5.64, 5.84, 5.77,
5.7, 5.82, 5.8, 5.97, 5.91, 5.5, 5.6, 5.72, 5.64, 5.7, 5.88,
6.07, 6, 6.02, 6.1, 6.1, 5.99, 6.05, 6.1, 6.11, 6.29, 6.27,
6.17, 6.2, 5.93, 5.95, 6.07, 6.22, 6.18, 6.34, 6.28, 6.43,
6.34, 6.3, 6.26, 6.38, 6.4, 6.25, 6.35, 6.25, 6.04, 6.25,
6.23, 6.07, 6.06, 5.95, 5.81, 5.83, 5.94, 5.98, 5.9, 5.72,
5.8, 5.85, 5.68, 5.74, 5.67, 6.06, 6.03, 5.88, 6.01, 6.16,
6.23, 6.03, 6.15, 6.16, 6.35, 6.33, 6.26, 6.38, 6.35, 6.3,
6.56, 6.61, 6.6, 6.7, 6.68, 6.78, 6.7, 6.64, 6.91, 6.93,
6.88, 7.02, 7.05, 7.09, 7.02, 6.95, 7, 6.77, 6.66, 6.58,
6.6, 6.65, 6.64, 6.6, 6.93, 6.7, 6.71, 6.59, 6.77, 7.1, 7.05,
7.06, 7.25, 7.02, 6.81, 6.76, 6.82, 6.76, 6.92, 6.96, 7.06,
7.06, 6.87, 6.92, 6.86, 6.88, 7.29, 7.35, 7.66, 7.62, 7.37,
7.26, 7.2, 7.66, 7.29, 6.93, 6.9, 6.82, 6.96, 6.7, 6.66,
6.67, 6.61, 6.26, 6.36, 6.45, 6.7, 6.7, 6.94, 7.02, 6.77,
7, 6.9, 6.81, 6.79, 7.14, 7.08, 7.12, 6.96, 6.82, 6.77, 6.82,
6.83, 6.88, 7.07, 7.06, 7.27, 7.33, 7.16, 7.52, 7.5, 7.5,
7.43, 7.5, 7.62, 7.48, 7.54, 7.51, 7.38, 7.3, 7.25, 7.28,
7.2, 7.22, 7.23, 7.26, 7.4, 7.38, 7.48, 7.58, 7.52, 7.54,
7.48, 7.45, 7.41, 7.43, 7.45, 7.52, 7.5, 7.36, 7.36, 7.42)),
class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA,
-500L))
tvec <- TVECM(price, nthresh = 2, lag = 2, ngridBeta = 300, ngridTh = 300, plot = TRUE, trim = 0.15)
#> Error in allgammas[seq(from = wh.thresh + ninter, to = length(allgammas) - : only 0's may be mixed with negative subscripts
Created on 2022-05-31 by the reprex package (v2.0.1)
@Justinxi , your example is unfortunately still not self-reproducible. :-( I thought the link How to make a great R reproducible example provided clear guidelines about reproducibility?
But well, can you please attach (in csv format) the smallest part of your dataset such that the error above happens?
good job! Now we have a reproducible example, and I confirm this is a bug. I will need to look into this