DynCorr | R Documentation |
Calculates the Dynamical Correlation for 2 paired dense regular functional data observed on the same grid.
DynCorr(x, y, t)
x |
a n by m matrix where rows representing subjects and columns representing measurements, missings are allowed. |
y |
a n by m matrix where rows representing subjects and columns representing measurements, missings are allowed. |
t |
a length m vector of time points where x,y are observed. |
A length n vector of individual dynamic correlations. The dynamic correlation can be obtained by taking average of this vector.
Dubin J A, Müller H G. Dynamical correlation for multivariate longitudinal data (2005). Journal of the American Statistical Association 100(471): 872-881. Liu S, Zhou Y, Palumbo R, Wang, J.L. (2016). Dynamical correlation: A new method for quantifying synchrony with multivariate intensive longitudinal data. Psychological methods 21(3): 291.
set.seed(10) n=200 # sample size t=seq(0,1,length.out=100) # length of data mu_quad_x=8*t^2-4*t+5 mu_quad_y=8*t^2-12*t+6 fun=rbind(rep(1,length(t)),-t,t^2) z1=matrix(0,n,3) z1[,1]=rnorm(n,0,2) z1[,2]=rnorm(n,0,16/3) z1[,3]=rnorm(n,0,4) x1_quad_error=y1_quad_error=matrix(0,nrow=n,ncol=length(t)) for (i in 1:n){ x1_quad_error[i,]=mu_quad_x+z1[i,]%*%fun+rnorm(length(t),0,0.01) y1_quad_error[i,]=mu_quad_y+2*z1[i,]%*%fun +rnorm(length(t),0,0.01) } dyn1_quad=DynCorr(x1_quad_error,y1_quad_error,t)
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