Parameter finding - can you give me a basic guide?

New Member
Hey there,

I started working with a detector, and I was asked to model the efficiency of this it. I have collected lots of data about the efficiency of this detector, and have lots of sampled datasets like efficiency vs "some important parameter". The number of important independent parameters is 6. What I want to achieve is to be able to give an answer to the question: "What would likely to be the efficiency if the 6 parameters were the following: (...)"?

Can you give me a basic guideline, how to approach this problem, or what kind of books I should try and read?

Thank you very much!

Stu

New Member
When you say efficiency, are you talking about statistical efficiency, or the efficiency of some physical sensor (i.e. detector) that is collecting data on something? If you are doing the latter, it sounds like you're doing basic scenario analysis, and simply need to change your input values to get estimates. For example, if you have a dataset:

Code:
DATASET
_______________________
y x1 x2 x3  b1  b2  b3
. 30 50 60  10  20  30
.  .  .  .  10  20  30
where b1, b2 and b3 are parameter estimates for x1, x2, and x3 respectively, you would simply put in custom values of x1-x3. Let's say you want to try two scenarios:

1. What if x1 increases by 10%, and x2 decreases by 5%?
2. What if x1, x2, and x3 are 15, 25, and 35?

For (1), take all known values of x1 and x2 and modify them, then multiply each by their parameter estimates.

For (2), create 3 new values for x1, x2, and x3, then multiply each by their parameter estimates.

Code:
DATASET
______________________________
y   x1   x2    x3  b1  b2  b3
.   33   47.5  60  10  20  30
.   15   25    35  10  20  30
y for scenario 1: (10*33) + (20*47.5) + (30*60)
y for scenario 2: (10*15) + (20*25) + (30*35)