# Computational Statistics & Data Analysis

Computational Statistics and Data Analysis > 1995 > 19 > 1 > 85-96

Computational Statistics and Data Analysis > 1995 > 19 > 1 > 59-74

Computational Statistics and Data Analysis > 1995 > 19 > 1 > 23-44

Computational Statistics and Data Analysis > 1995 > 19 > 1 > 75-83

Computational Statistics and Data Analysis > 1995 > 19 > 1 > 45-52

_{1}nonlinear curve-fitting. It is based on the smooth approximation in arbitrarily small neighborhoods of the points of discontinuous differentiability caused by the absolute value operator. Such a smooth approximation can be minimized using efficient algorithms in L

_{2}norm. The approximate function in the arbitrarily...

Computational Statistics and Data Analysis > 1995 > 19 > 1 > 53-58

Computational Statistics and Data Analysis > 1995 > 19 > 1 > 1-21

Computational Statistics and Data Analysis > 1995 > 19 > 2 > 129-134

Computational Statistics and Data Analysis > 1995 > 19 > 2 > 223-234

Computational Statistics and Data Analysis > 1995 > 19 > 2 > 191-201

Computational Statistics and Data Analysis > 1995 > 19 > 2 > 135-148

Computational Statistics and Data Analysis > 1995 > 19 > 2 > 115-128

Computational Statistics and Data Analysis > 1995 > 19 > 2 > 149-153

Computational Statistics and Data Analysis > 1995 > 19 > 2 > 155-175

Computational Statistics and Data Analysis > 1995 > 19 > 2 > 177-189

Computational Statistics and Data Analysis > 1995 > 19 > 3 > 321-326

Computational Statistics and Data Analysis > 1995 > 19 > 3 > 309-319

Computational Statistics and Data Analysis > 1995 > 19 > 3 > 327-349

Computational Statistics and Data Analysis > 1995 > 19 > 3 > 265-282

^{3}log n) computations and O(n

^{2}) storage. The idea is to compute the least squares (LS) estimate for O(n

^{2}) subsets of size h (and...