R help - Aug 2013 - VAR function in vars package: find the standard deviation of the error

Hi,

   Does someone know how to find the standard deviation of the error term
in the VAR object? The whole structure of the VAR is attached.


   Thanks,
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structure(list(varresult = structure(list(dlfx = structure(list(
    coefficients = structure(c(0.00813806346620756, 0.00194118750380967, 
    0.0356273560028057, -0.00201411510115263, -0.00543118752499316
    ), .Names = c("dlfx.l1", "flow.l1", "dlfx.l2",
"flow.l2",
    "const")), residuals = structure(c(0.0561549050928879,
0.0208505573686644,
    0.0190577910133913, -0.304598370814063, 0.0383133465626951, 
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5.96, 0.49, -6, -2.54, 1.47, -0.92, -0.07, 1.22, -0.32, -0.38, 
5.4, 4.59, 2.7, 0.72, 3.56, 0.09, 1.09, 3.26, 0.92, 0.49, 2.89, 
2.98, 1.79, 0.93, 0.76, 2.64, 1.43, 3.84, 1.99, -4.11, 1.23, 
-0.45, 2, 0.86, -2.69, -1.43, -0.22, -0.66, -1.14, 1.84, 2.11, 
2.99, 6.02, 0.7, 4.75, 3.96, 4, 0.6, 3.49, 0.38, -0.85, 3.53, 
-2.12, -1.45, -2.86, -1.29, -2.73, -1.95, 1.77, 1.7, 2.19, 1.07, 
-2.28, -0.13, -0.5, 0.08, -0.51, 3.02, 4.35, 1.95, 1.21, 0.82, 
7.59, 0.64, 2.81, 3.41, 1.5, 0.16, 4.14, 0.08, -3.3, 0.56, 1.69, 
-0.44, 2.75, 1.61, 2.81, 1.09, 3.14, 0.67, 1.51, -2.05, -1.69, 
-3.79, 1.16, 4.11, 3.32, 5.47, 2.43, -0.35, 2.12, 1.98, 2.21, 
-1.08, -0.98, 1.67, 3.11, 3.43, 3.86, -7.16, 0.39, 15.75, 0.26, 
-2.64, -6.02, -5.91, -5.46, -1.28, 2.42, 3.19, -7.11, -0.19, 
-6.12, -2.46, -0.35, -0.3, -2.24, -0.55, -0.43, 0.69, 1.18, 0.12, 
-1.97, -1.38, -2.87, -1.6, -1.68, -3.13, -2.08, -0.54, -2.15, 
0.38, 0.95, 2.12, 2.47, 2.84, 2.05, 3.81, 0.8, 8.05, 3.24, 3.6, 
5.04, -1.79, -2.66, 0.64, 0.41, -2.86, -0.81, 1.66, 3.84, 2.53, 
2.43, 2.89, 3.61, 12.69, 4.28, 2.57, -0.27, -1.73, 0.02, 1.56, 
2.96, 2.79, 4.52, -2.66, -2.3, -1.64, -0.56, 2.19, 0.56, -1.37, 
-7.47, 0.56, -2.17, 2.84, -0.07, 4.3, 3.14, 2.62, -2.23, -1.03, 
-1.71, 1.96, 2.61, -1.25, -1.21, 3.02, -2.97, -5.14, -3.56, 1.65, 
0.8, 2.16, 1.07, -0.39, 0.07, 2.89, 3.84, 2.18, -2.74, 1.82, 
1.28, -0.35, -0.25, -1.26, -4.95, -3.47, -2.07, -2.48, -2.97, 
-9.79, -2.61, 0.4, -0.61, 0.6, 1.52, -0.04, -1.42, -2.79, -0.96, 
-1.95, -2.74, -7.73, -4.48, -5.74, -7.37, -10.59, -11.36, -1.3, 
-4.65, -0.67, -2.16, -6.78, -3.2, -5.78, -0.82, -2.32, -2.48, 
-1.56, -0.94, 1.67, 3.82, -0.02, 1.22, -7.34, -3.21, -5.63, -3.36, 
-3.99, -3.55, -4.32, -4.21, 2.23, -1.08, -1.13, -1.44, -1.81, 
-6.49, -6.13, 1.3, 1.64, -0.24, -0.99, -4.89, -4.53, -2.38, 1.33, 
0.9, 1.87, 1.93, 0.8, 0.14, 2.32, 1.96, -0.5, -5.72, -5.4, 3.85, 
1.6, 0.04, 1.08, 10.43, 2, -0.28, -0.47, -1.53, -1.98, -0.16, 
-0.34, -1.75, 1.47, -5.79, 0.07, 0.44, 0.25, -0.47, -1.88, -2.5, 
-2.33, 1.05, -6.79, -2.77, -1.63, 3.84, 3.4, 2.35, 0.93, 0.5, 
-0.52, 0.08, 0.53, -0.5, -0.26, 1.59, -1.95, -0.99, -3.45, -1.14, 
-1.39, 0.61, 1.67, 0.91, -2.68, 0.81, 0.81, 1.21, 1.5, 0.87, 
-0.29, -0.71, 2.05, 0.59, -0.01, 3.02, 4.62, 3.21, 2.36, 1.32, 
2.14, 2.57, -6.15, 0.18, 12.77, 3.31, -3.69, 1.27, 1.03, -2.12, 
2.15, 3.07, 2.03, -2.94, 0.32, -2.93, -1.13, 1.88, 5.82, 1.26, 
-4.6, 1.01, 1.58, 1.78, 9.99, 3.25, 0.93, -3.62, -0.55, -0.23, 
-1.36, -1.21, 0.61, 0.71, 2.65, 3.54, 1.79, 0.23, 1.72, 0.22, 
2.36, 0.76, 1, -0.63, -0.13, 1.62, 2.92, 0.32, -2.3, 2.37, 0.08, 
-2.71, -2.95, -0.49, -1.04, -0.58, -0.97, 0.71, -0.58, -2.57, 
-0.69, 1.03, -0.03, 0.39, 0.87, -0.06, 5.01, 0.93, 1.9, -3.75, 
1.12, 1.26, -5.14, -3.91, -2.01, -2.84, -3.84, -1.92, -2.61, 
-5.9, -0.25, -5.17, 1.36, -0.29, -2.31, 0.87, -3.75, 0.85, 1.4, 
-0.1, -5.68, -4.1, -0.6, -0.17, -0.96, -0.74, 0.39, -0.99, -0.25, 
3.04, 1.75, -0.28, 3.19, 2.75, -0.29, -0.15, -1.43, -0.18, 0.15, 
-0.76, 3.23, 2.7, 1.36, -2.29, 0.75, -1.06, -1, -2.34, -2.5, 
-2.38, -4.02, -1.32, 0.05, -0.39, -2.46, -1.45, 0.32, -6.01, 
-2.32, -5.13, -0.92, -0.85, 0.42, -0.98, -0.24, 0.58, 1.39, 3.28, 
3.13, 1.87, 0.65, 2.48, 0.48, 0, 0.74, -0.61, 3.33, -0.64, -0.86, 
-0.27, -0.94, -0.95, -0.47, 3.34, 1.47, -4.03, -0.6, 0.28, -2.74, 
0.3, 1.48, -0.5, 0.12, -0.3, 4.21, 2.42, -2.33, -0.3, 0.5, 1.95, 
0.36, 1.19, 0.15, 0.31, 2.09, -0.76, 1.07, 0.47, 2.1, 1.27, 0.7, 
0.67, 1.59, -3.34, -0.89, 2.01, -0.87, -1.46, 0.67, -3.15, -1.04, 
-0.38, 0.87, 0.62, -0.57, 1.04, 0.54, 0.39, -0.53, -0.48, -1.91, 
3.39, 3.48, 1.3, -0.13, -0.52, -0.57, -3.5, -1.04, -0.54, 0.35, 
1.38, -2.21, 2.13, 3.32, 2.54, 2.61, 1.35, 5.4, 3.51, -0.86, 
1.1, 3.05, 1.17, 1.24, 2.77, 1.67, 1.59, 2.9, -0.04, -1.1, 1.88, 
1.76, 1.28, -4.06, 0.52, -0.73, 1.85, 1.23, 2.25, 1.11, 2.94, 
-0.24, -3.79, -1.99, 0.4, 2.26, -0.89, 2.39, -0.31, 1.1, 2.13, 
1.87, -4.96, -0.11, 0.66, 0.14, -1.32, -1.01, -1.38, 2.49, 3.86, 
-0.42, 2.16, 3.4, 2.46, -3.37, 0.48, 5.78, 1.18, 2.56, 3.3, 0.79, 
-5.54, 0.77, 2.17, 1.08, 0.49, -1.43, -1.99, 0.4, 2.26, 0.72, 
0.33, 1.51, -1.89, 1.27, -2.02, -2.02, -2.29, -2.03, -2.57, -2.44, 
1.75, 1.4, 0.66, -1.53, 0.04, 0.92, 1.38, 1.68, -3.16, -1.87, 
-0.21, 0.63, -1.7, 1.36, 1.15, 1.23, 0.39, 2.53, -0.23, -0.14, 
1.59, 2.76, 3.5, 6.55, 1.63, -1.36, -0.67, 4.86, 3.27, 4.25, 
2.55, -1.01, 1.15, 3.71, 2.21, -0.48, -2.12, 0.79, 3.1, 1.28, 
1.11, -7.76, 0.59, 0.07, -0.17, -0.36, -6.06, -1.3, 0.01, 3.25, 
-1.4, -0.27, -1.28, -2.91, -3.61, -1.42, -0.67, -3.18, -0.29, 
0.34, -10.99, -4.25, 1.18, 0.53), .Dim = c(871L, 2L), .Dimnames = list(
    NULL, c("dlfx", "flow"))), type = "const", p =
structure(2L, .Names = "SC(n)"),
    K = 2L, obs = structure(869L, .Names = "SC(n)"), totobs =
structure(871L, .Names = "SC(n)"),
    restrictions = NULL, call = quote(VAR(y = y_dl, type = "const", 
        lag.max = 30, ic = "SC"))), .Names = c("varresult",
"datamat",
"y", "type", "p", "K", "obs",
"totobs", "restrictions", "call"
), class = "varest")

library(vars)
data(Canada)
mod <- VAR(Canada, p = 2, type = "both")
apply(resid(mod), 2, sd)

See also, ?summary and in particular the returned list element 'covres'.

HTH,
Bernhard

-----Urspr?ngliche Nachricht-----
Von: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] Im
Auftrag von jpm miao
Gesendet: Freitag, 2. August 2013 11:11
An: r-help
Betreff: [R] VAR function in vars package: find the standard deviation of the
error

Hi,

   Does someone know how to find the standard deviation of the error term in the
VAR object? The whole structure of the VAR is attached.


   Thanks,
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