Hi there,
I’m still working on the restricted OLS regressions and in the meantime even uploaded an early version of a function package that uses a SQP of GNU R and a bootstrap routine to get coeffs and standard errors.
In order to produce a nice show case of the optimization problem I generate all combination of coefficients with a step size of n. If there are 3 coeffs that are >=0 and should sum up to 1 the matrix can be easily generated via loop. Since gretl has a special "for loop" one could use this loop version in order to fill the percentages in the matrix in one step. However, there is a bug. Have a look. I’m using the current x64 snapshot for windows.
Cheers and a nice first Sunday in Advent
Leon
<hansl>
scalar intN_1_a = 50 # step size of 2 percent
scalar intStep = 1/intN_1_a
eval intStep
matrix mCombis = NA
matrix mCombisALL = NA
set stopwatch
loop for i=0..intN_1_a --quiet
loop for j=0..intN_1_a --quiet
if i+j<=intN_1_a
if i+j == 0
mCombisALL = i ~ j ~ (intN_1_a-i-j)
else
mCombisALL |= i ~ j ~ (intN_1_a-i-j)
endif
endif
endloop
endloop
eval $stopwatch/60
eval rows(mCombisALL)
# correct number of rows since
scalar intSum3 = (intN_1_a)*3 + (1+intN_1_a-3+1)*(1+intN_1_a-3)/2
# for three coeefs I found this closed formula, with more it’s another…
eval intSum3
set stopwatch
loop for (i=0; i<=1; i+=intStep) --quiet
loop for (j=0; j<=1; j+=intStep) --quiet
if i+j<=1
if i+j == 0
mCombis = i ~ j ~ (1-i-j)
else
mCombis |= i ~ j ~ (1-i-j)
endif
endif
endloop
endloop
eval rows(mCombis)
eval $stopwatch
# correct number
scalar intSum3 = (intN_1_a)*3 + (1+intN_1_a-3+1)*(1+intN_1_a-3)/2
eval intSum3
# wrong, WHY? The reason has to do with the.xx999 values and the missing 1s.
<hansl>
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