Using Extraneous Information and GMM to Estimate Threshold Parameters in TAR Models

Using neural network to estimate weibull parameters

As is well known, estimating parameters of the tree-parameter weibull distribution is a complicated task and sometimes contentious area with several methods vying for recognition. Weibull distribution involves in reliability studies frequently and has many applications in engineering. However estimating the parameters of Weibull distribution is crucial in classical ways. This distribution has t...

Using Neural Nets to Estimate Evolutionary Parameters

The rapid growth in the amount of molecular genetic data being collected will, in many cases, require the development of new analytic methods for the analysis of that data. In this paper we explore the feasibility of using machine learning algorithms, in particular neural networks, to estimate two evolutionary parameters of great interest: mutation and recombination rates. We show that this is ...

using neural network to estimate weibull parameters

as is well known, estimating parameters of the tree-parameter weibull distribution is a complicated task and sometimes contentious area with several methods vying for recognition. weibull distribution involves in reliability studies frequently and has many applications in engineering. however estimating the parameters of weibull distribution is crucial in classical ways. this distribution has t...

Comparison Comparison PCA Train GMM Feature Reduction Classify GMM Threshold

A new approach to face verification from 3D data is presented. The method uses 3D registration techniques designed to work with resolution levels typical of the irregular point cloud representations provided by Structured Light scanning. Preprocessing using a-priori information of the human face and the Iterative Closest Point algorithm are employed to establish correspondence between test and ...

Using Hierarchical Models to Estimate a Weighted Average of Stratum-specific Parameters