JMLR
2008
14 years 11 days ago
2008
Pointwise consistent, feasible procedures for estimating contemporaneous linear causal structure from time series data have been developed using multiple conditional independence ...
CSDA
2007
14 years 12 days ago
2007
Vector autoregressive (VAR) modelling is one of the most popular approaches in multivariate time series analysis. The parameters interpretation is simple, and provide an intuitive...
CORR
2007
Springer
14 years 12 days ago
2007
Springer
Similarity search is an important problem in information retrieval. This similarity is based on a distance. Symbolic representation of time series has attracted many researchers re...
CORR
2007
Springer
14 years 12 days ago
2007
Springer
Here, we present a family of time series with a simple growth constraint. This family can be the basis of a model to apply to emerging computation in business and micro-economy wh...
IS
2008
14 years 12 days ago
2008
Performing data mining tasks in streaming data is considered a challenging research direction, due to the continuous data evolution. In this work, we focus on the problem of clust...
BMCBI
2007
14 years 13 days ago
2007
Time course gene expression experiments are a popular means to infer co-expression. Many methods have been proposed to cluster genes or to build networks based on similarity measu...
BMCBI
2007
14 years 13 days ago
2007
Background: Microarray time series studies are essential to understand the dynamics of molecular events. In order to limit the analysis to those genes that change expression over ...
BMCBI
2007
14 years 13 days ago
2007
Background: Periodogram analysis of time-series is widespread in biology. A new challenge for analyzing the microarray time series data is to identify genes that are periodically ...
DATAMINE
2006
14 years 13 days ago
2006
With the growing importance of time series clustering research, particularly for similarity searches amongst long time series such as those arising in medicine or finance, it is cr...
CSDA
2006
14 years 13 days ago
2006
We explore a periodic analysis in the context of unobserved components time series models that decompose time series into components of interest such as trend, seasonal and irregu...