I have three sets of data, measured by three different devices: A,B
and C
of air balloon whose fall is influenced by wind and each data sheet looks like;
A:
Longitude Latitude Altitude Weight Rotation(about main axis) Time
... ... ... ... ... ...
B:
Longitude Latitude Altitude Weight Rotation(about main axis) Time
... ... ... ... ... ...
and similarly for C
.
Are there known standard techniques to compute the error in measurement of B
and C
with respect to A
(considered standard)?.
Note that except time, all other parameter can both increase and decrease and longitude/latitude and rotation are only parameters that can be positive and negative.
The problem with regression is that I do not have independent/dependent variables. The method of error analysis I generally approach is calculate $Err_{x},Err_{y},Err_{z}$ and combine them suitably when I have a function explaining something. I do not have a function to propagate error from given quantities.
ADDED
By combining using a suitable function, I mean : computing error of all quantities individually and propagating the error.
I am trying to measure accuracy of the devices B
(let's disregard C for now) taking A
as standard.