search for: constaints

Hello: I have been trying to program the following maximization problem and would definitely welcome some help. the target function: sum_{i} f(alpha, beta'X_{i}), where alpha and beta are unknown d-dim parameter, f is a known function an X_{i} are i.i.d. r.v. I need to maximize the above sum, under the constaint that:

Hi All, I have a sample x={x1,x2,..,xn} fom a distribution with density f. I wish to estimate the density. I know a priori that the density is monotonically decreasing. Is there a way to do this in R? Thanks Debayan

...st and CRAN but couldn't find anything that would help me (Tps in fields is too slow, cobs would be really nice but seems to be one-dimensional). Is there any package that would at least give me the basis for multidimensional b-splines? Or even one that would do the fitting, perhaps even with constaints on derivatives at the edges (which I can specify from theory)? Thank you, Tamas -- Bayesian statistics is difficult in the sense that thinking is difficult. --Donald A. Berry, American Statistician 51:242 (1997)

Hi, i need to minimize a quadratic function with boundary condidtions and one equality condition. In order to do that i converted the equality constraint into 2 inequality constaints and passed everything cia constrOptim, as the manual said: everything included in the ... will be passed to Optim that will pass it back to fn in case it does not need it. My code is the following: mat <- array( c(0.0001088799073581, 0.0000136029502036, 0.0000060430384243, 0.0000847097879033,...

Here''s the situation: I have a "people" table whose "id" column serves as a foreign key to several other tables (authorships, editorships, members, users, etc.). Every now and then I will find two distinct records in the "people" table that represent the same human being. They generally differ by small differences in spelling but should really be the