# Significance of transfer entropy calculations

I have two time-series U and V (approximately 300 samples) having values between 0 and 5. I wanted to calculate the (first order) transfer entropy $I_{uv}$ (of U with the knowledge of V) and $I_{vu}$ (of V with the knowledge of U). Here are the values I got :

$I_{uv}$ = 0.1492 and $I_{vu}$ = 0.1342

Since these values are close to each other, I started questioning their significance. Thus, I calculated the transfer entropy $I_{u-rv}$ of U with the knowledge of a randomized (in time) version of V, and the transfer entropy $I_{v-ru}$ of V with the knowledge of a randomized (in time) version of U. I calculated 500 values of $I_{u-rv}$ and $I_{v-ru}$, which gave me :

mean($I_{u-rv}$ ) = 0.1218 - standard deviation = 0.0198

mean($I_{v-ru}$) = 0.1019 - standard deviation = 0.0198

The values of $I_{uv}$ and $I_{vu}$ lie close to (mean+std) so I would say there is an influence of one time serie on the other. From these information what can really be said about the two time-series ? (I will upload a picture of these time-series as soon as I figure a way to do it)