BillJosephson wrote:
Hello, on pages 4 and 5 of the chapter "The General Linear Model"
(Kiebel and Holmes) found in Human Brain Function (and at
http://www.fil.ion.ucl.ac.uk/spm/doc/books/hbf2/),
I do not understand what T is:
In the exposition, a matrix form is offered. It shows column matrix
[Y1...Yj...YJ] =
rectangular matrix
[ x11 ... x1l ... x1L
xj1 ... xjl ... xjL
xJ1 ... xJl ... xJL ]
by column matrix (B is beta)
[B1 ... Bl ... BL]
plus column matrix
[e1 ... el ... eJ]
It defines the terms:
Y is the column vector of observations
e is the column vector of error terms
B is the column vector of parameters; B = [B1, ... ,Bl, ... , BL]^T
I understand everything except the exponent T. What is it? Soon after
it appears throughout the equations, which I don't understand because I
don't understand what it means above.
Thanks much in advance for any understanding....
[B1, B2, ..., BL] a row vector.
[B1, B2, ..., BL]^T is the corresponding column vector.
More generally, M^T is the transpose of M,
where M is a matrix or vector.
