Parametric statistics

About: Parametric statistics is a research topic. Over the lifetime, 39200 publications have been published within this topic receiving 765761 citations.

Maximum likelihood estimation for social network dynamics

Abstract: A model for network panel data is discussed, based on the assumption that the observed data are discrete observations of a continuous-time Markov process on the space of all directed graphs on a given node set, in which changes in tie variables are independent conditional on the current graph. The model for tie changes is parametric and designed for applications to social network analysis, where the network dynamics can be interpreted as being generated by choices made by the social actors represented by the nodes of the graph. An algorithm for calculating the Maximum Likelihood estimator is presented, based on data augmentation and stochastic approximation. An application to an evolving friendship network is given and a small simulation study is presented which suggests that for small data sets the Maximum Likelihood estimator is more efficient than the earlier proposed Method of Moments estimator.

Nonparametric Regression Analysis of Growth Curves

Abstract: In recent years, nonparametric curve estimates have been extensively explored in theoretical work. There has, however, been a certain lack of convincing applications, in particular involving comparisons with parametric techniques. The present investigation deals with the analysis of human height growth, where longitudinal measurements were collected for a sample of boys and a sample of girls. Evidence is presented that kernel estimates of acceleration and velocity of height, and of height itself, might offer advantages over a parametric fitting via functional models recently introduced. For the specific problem considered, both approaches are biased, but the parametric one shows qualitative and quantitative distortion which both are not easily predictable. Data-analytic problems involved with kernel estimation concern the choice of kernels, the choice of the smoothing parameter, and also whether the smoothing parameter should be chosen uniformly for all subjects or individually.

Optical parametric oscillator frequency tuning and control

Abstract: The frequency-tuning and -control properties of monolithic doubly resonant optical parametric oscillators are analyzed for stable single-mode pump radiation. Single-axial-mode operation is observed on the idler and the signal for both pulsed and continuous pumping. Projections are made for tuning-parameter tolerances that are required for maintenance of stable single-frequency oscillation. Continuous frequency tuning is possible through the simultaneous adjustment of two or three parameters; thus the synthesis of specific frequencies within the broad tuning range of the doubly resonant optical parametric oscillator is permitted.