Sequential density

Sequential nonparametric density estimation

Reconstruction of sequential data with density models

We introduce the problem of reconstructing a sequence of multidimensional real vectors where some of the data are missing. This problem contains regression and mapping inversion as particular cases where the pattern of missing data is independent of the sequence index. The problem is hard because it involves possibly multivalued mappings at each vector in the sequence, where the missing variabl...

Sequential change-point detection based on direct density-ratio estimation

Change-point detection is the problem of discovering time points at which properties of time-series data change. This covers a broad range of real-world problems and has been actively discussed in the community of statistics and data mining. In this paper, we present a novel nonparametric approach to detecting the change of probability distributions of sequence data. Our key idea is to estimate...

A Sequential Monte Carlo/Time-Dependent Density Functional Theory

A transição eletrônica n * do formaldeído em água é analisada usando-se um procedimento combinado e seqüencial de Monte Carlo (MC) clássico e mecânica quântica (MQ). MC é usado para gerar configurações do líquido para uso posterior em cálculos de MQ. Usando-se a representação espectral da teoria do funcional da densidade com uma base de funções gaussianas localizadas (TD-DFT/6-311++G(d,p)) cálc...

Mixture Density Estimation Based on Maximum Likelihoodand Sequential Test

We address the problem of estimating an unknown probability density function from a sequence of input samples. We approximate the input density with a weighted mixture of a nite number of Gaussian kernels whose parameters and weights we estimate iteratively from the input samples using the Maximum Likelihood (ML) procedure. In order to decide on the correct total number of kernels we employ sim...