print.susy.Rd
Prints information about an susy
object.
# S3 method for susy
print(x, corr.no.abs=TRUE, legacy=FALSE, ...)
A susy
object.
Logical, defaults to TRUE
display correlation without the absolute value.
Logical, defaults to FALSE
, when TRUE
print will produce an output that matches the output of legacy SUSY implementation.
Extra arguments passed to print.data.frame
method.
Returns x
invisibly. Display output to console as a side effect.
n = 1000
data = data.frame(
var1 = runif(n, 300, 330),
var2 = runif(n, 300, 330)
)
res = susy(data, segment=30L, Hz=15L)
res
#> Var1 Var2 n(data) Z Z-Pseudo SD(Z) SD(Z-Pseudo) n(lags)
#> 1 var1 var2 1000 0.03754926 0.03472075 0.0189501 0.01999434 91
#> %>Pseudo n(Segmente) ES Z(lead1) Z(lead2) ES(lead1) ES(lead2)
#> 1 58.24176 2 0.1414657 0.03447701 0.04096418 0.02658748 0.2485895
#> meanZ(in-phase) meanZ(anti-phase) Anzahl(in-phase) Anzahl(anti-phase)
#> 1 0.02817847 -0.02612137 34 57
#> Z(noAbs) Z(Pseudo-noAbs) %>Pseudo(noAbs) ES(noAbs)
#> 1 -0.005833517 0.006605475 36.26374 -0.3838489
print(res, corr.no.abs=FALSE)
#> Var1 Var2 n(data) Z Z-Pseudo SD(Z) SD(Z-Pseudo) n(lags)
#> 1 var1 var2 1000 0.03754926 0.03472075 0.0189501 0.01999434 91
#> %>Pseudo n(Segmente) ES Z(lead1) Z(lead2) ES(lead1) ES(lead2)
#> 1 58.24176 2 0.1414657 0.03447701 0.04096418 0.02658748 0.2485895
print(res, digits=4)
#> Var1 Var2 n(data) Z Z-Pseudo SD(Z) SD(Z-Pseudo) n(lags) %>Pseudo
#> 1 var1 var2 1000 0.03755 0.03472 0.01895 0.01999 91 58.24
#> n(Segmente) ES Z(lead1) Z(lead2) ES(lead1) ES(lead2) meanZ(in-phase)
#> 1 2 0.1415 0.03448 0.04096 0.02659 0.2486 0.02818
#> meanZ(anti-phase) Anzahl(in-phase) Anzahl(anti-phase) Z(noAbs)
#> 1 -0.02612 34 57 -0.005834
#> Z(Pseudo-noAbs) %>Pseudo(noAbs) ES(noAbs)
#> 1 0.006605 36.26 -0.3838
print(res, legacy=TRUE)
#> Var1 Var2 n(data) Z Z-Pseudo SD(Z) SD(Z-Pseudo) n(lags) %>Pseudo n(Segmente) ES Z(lead1) Z(lead2) ES(lead1) ES(lead2) meanZ(in-phase) meanZ(anti-phase) Anzahl(in-phase) Anzahl(anti-phase) Z(noAbs) Z(Pseudo-noAbs) %>Pseudo(noAbs) ES(noAbs)
#> var1 var2 1000 0.03754926 0.03472075 0.0189501 0.01999434 91 58.24176 2 0.1414657 0.03447701 0.04096418 0.02658748 0.2485895 0.02817847 -0.02612137 34 57 -0.005833517 0.006605475 36.26374 -0.3838489