In article <91715h$sbv$[EMAIL PROTECTED]>,
 "junk" <[EMAIL PROTECTED]> writes:
snip
|> Why I am trying to do is come up with a simple method of doing a
|> multivariable (multidimensional ?) least squares approximation.
|> 
|> How could I easily create:
|> Y = (a1*A^4 + b1*A^3 . e1*A + f1)  + (a2*B^4 .. + f2)  + (a3*C^4 +.+f3)
the model is wrong! replace f1+f2+f3 by _one- f

snip

 I hope EXCEL has a linear system solver which works correctly.
 (Off limits for MS here)
 In this case  set up a matrix  "M"  with 13 columns and 
 with rows 
 [ A^4 A^3 A^2 A  B^4 B^3 B^2 B  C^4 C^3 C^2 C 1 ] 
inserting the values of A,B and C from one row of your data file
also set up a vector "n" of all Y's, 
In your case "M"  has  18 rows (not that much for 13 parameters !)
Now solve 

  M'M [x] = M'n 
this is a linear system of equations with 13 equations and 13 unknowns [x]
M' means transposition . e.g. element (13,13) of M'M is 18. 
solve the system. then
[x]=(a1,b1,c1,d1,a2,b2,c2,d2,a3,b3,c3,d3,f)
If your data points are not properly distributed in space, then it may turn out
that the matrix is singular (for example you must not have all data points with
A=B=C). In that case you need more points  resp. better distributed points.

just for curiosity: with the meaning of A=paint, B=engine, C=amenities 
Y=price, why do you assume this linear behaviour with respect to the
influences of A,B,C but such a strange behaviour in powers of A,B,C alone?
shouldn't the influence of "C" show some saturation effect? 

hope that helps

peter

 

|> A        B          C                Y
|> paint engine amenities price
|> 0.1      1      6    $1000
|> 0.11    2    5      1200
|> 0.14    1    3      1150
|> 0.16    2    5      1200
|> 0.2      1    4      3000
|> 0.201  4    5      2700
|> 0.3      2      3      4000
|> 0.33    4      7      3500
|> 0.35    1      4      6000
|> 0.4      2      6      4650
|> 0.41    3      4      4400
|> 0.42    4    3      4750
|> 0.44    1    5      5360
|> 0.45    1    3      7500
|> 0.6      3    3      7400
|> 0.8      2    5      7700
|> 0.87    2      6      8500
|> 0.88    3      5      9000


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