Two new stochastic search methods are proposed for optimizing the knot locations and/or smoothing parameters for least-squares or penalized splines. One of the methods is a golden-section-augmented blind search, while the other is a continuous genetic algorithm. Monte Carlo experiments indicate that the algorithms are very successful at producing knot locations and/or smoothing parameters that are near optimal in a squared error sense. Both algorithms are amenable to parallelization and have been implemented in OpenMP and MPI. An adjusted GCV criterion is also considered for selecting both the number and location of knots. The method performed well relative to MARS in a small empirical comparison.

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Responses for 2,012 Grandparent Strengths and Needs Inventories (GSNI) by grandparents, parents, and grandchildren were factor analyzed to determine if the underlying structure of the instrument fit the hypothesized dimensions suggested by the position of 60 items on six subscales. Two extraction methods, principal components and principal factors analyses, produced 10 factors with prerotation eigenvalues greater than 1.0. A principal component solution set at six factors yielded the "best fit," accounting for 49.2% of the variance. The pattern of item-to-factor correlation suggested that the 60 items tended to fit the hypothesized pattern of subscales. Empirical evidence supported the presence of six dimensions: (a) satisfaction, (b) success, (c) teaching, (d) difficulty, (e) frustration, and (f) information needs as constructs comprising the six subscales of the GSNI.

Abstract. The RngStreams software package provides one viable solution to the problem of creating independent random number streams for simulations in parallel processing environments. Techniques are presented for effectively using RngStreams with C++ programs that are parallelized via OpenMP or MPI. Ways to access the backbone generator from RngStreams in R through the parallel and rstream packages are also described. The ideas in the paper are illustrated with both a simple running example and a Monte Carlo integration application. NOTICEThis is a preprint of an article appearing in Computational Statistics (in press). The final publication is available at http://dx