Chia C Chong [EMAIL PROTECTED] wrote in message
a145qk$qfq$[EMAIL PROTECTED]">news:a145qk$qfq$[EMAIL PROTECTED]...
Hi!
I have a series of observations of 2 random variables (say X and Y) from my
measurement data. These 2 RVs are not independent and hence f(X,Y) ~=
f(X)f(Y). Hence, I can't
In article a145qk$qfq$[EMAIL PROTECTED],
Chia C Chong [EMAIL PROTECTED] wrote:
Hi!
I have a series of observations of 2 random variables (say X and Y) from my
measurement data. These 2 RVs are not independent and hence f(X,Y) ~=
f(X)f(Y). Hence, I can't investigate f(X) and f(Y) separately. I
Hi!
I have a series of observations of 2 random variables (say X and Y) from my
measurement data. These 2 RVs are not independent and hence f(X,Y) ~=
f(X)f(Y). Hence, I can't investigate f(X) and f(Y) separately. I tried to
plot the 2-D kernel density estimates of these 2 RVs and from the it
Chia C Chong [EMAIL PROTECTED] wrote in message
a145qk$qfq$[EMAIL PROTECTED]">news:a145qk$qfq$[EMAIL PROTECTED]...
Hi!
I have a series of observations of 2 random variables (say X and Y)
from my
measurement data. These 2 RVs are not independent and hence f(X,Y) ~=
f(X)f(Y). Hence, I can't
