print.susy.RdPrints 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