Hotbirdym
May2-11, 10:12 AM
Hi,
I've asked this question on another forum, but no response until now. Maybe I will have a little bit of luck here. So .. I have a problem. I have a set of 8 parameter and I use this parameters in order to compute a measure (I vary each parameter with a step of 50%). I would like to know how these parameters influence the measure, which one has the highest loading on the measure that I must compute.
First I looked at PCA, but now I think this is not for my problem. Why? When I compute the correlation matrix I see that the correlation between parameters is almost 0 ( 1*pow(10, -20) ) which I consider to be 0. If the correlation is 0 then I tend to believe that they are independent so I need to use a different multivariate analysis method. Also, the correlation between each parameter and the measure is quite high, something like 0.50 or -0.70 and thus I conclude that they are high correlated. So I thought of using MLR. Am I right or not?
I think I have too many parameters and I've reduced the ones which have the lowest correlation with the measure (I've chosen the value for this parameters the highest - 100%) and now I have only 5 parameters.
Please correct me if I am wrong on choosing MLR method or suggest me another method to use in order to compute the influence each parameter has on my measure.
Many thanks,
Elena
I've asked this question on another forum, but no response until now. Maybe I will have a little bit of luck here. So .. I have a problem. I have a set of 8 parameter and I use this parameters in order to compute a measure (I vary each parameter with a step of 50%). I would like to know how these parameters influence the measure, which one has the highest loading on the measure that I must compute.
First I looked at PCA, but now I think this is not for my problem. Why? When I compute the correlation matrix I see that the correlation between parameters is almost 0 ( 1*pow(10, -20) ) which I consider to be 0. If the correlation is 0 then I tend to believe that they are independent so I need to use a different multivariate analysis method. Also, the correlation between each parameter and the measure is quite high, something like 0.50 or -0.70 and thus I conclude that they are high correlated. So I thought of using MLR. Am I right or not?
I think I have too many parameters and I've reduced the ones which have the lowest correlation with the measure (I've chosen the value for this parameters the highest - 100%) and now I have only 5 parameters.
Please correct me if I am wrong on choosing MLR method or suggest me another method to use in order to compute the influence each parameter has on my measure.
Many thanks,
Elena