TSPAC Homepage
Prof. Stanley L. Sclove (312) 996-2681
IDS Dept. (MC 294) (312) 996-2676
UIC
601 S. Morgan St.
Chicago, IL 60607-7124
slsclove@uic.edu
www.uic.edu/~slsclove
TSPAC (Time Series Segmentation Package)
is a package of computer programs for time-series segmentation.
The current TSPAC programs use one-step ahead Bayesian classification.
This is a greedy algorithm which is suboptimal.
The programs will be further developed to include the Viterbi
algorithm.
Some further documentation on the algorithm
for TSPAC is available: ASCII text version
MS Word version.
TSPAC programs
The programs are classified according to
- the number of variables
- 1 or p
- the mode
- automatic: a range of values for K, the number of states, is input; not automatic: a single value of
K is input
- the transition matrix
- sparse (transition allowed only to adjacent states) or not
Links to source code of individual programs
-
TSSG1CMA
- 1 variable, common
variance, automatic mode
-
TSSG1CAS
- 1 variable, common
variance, automatic mode, sparse transition matrix
-
TSSG1DT
- 1 variable, different variances
-
TSSG1DTA
- 1 variable, different variances,
automatic mode
-
TSSGPDTA
- P variables, different covariance matrices,
automatic mode
TSPAC is part of a suite of programs called
ISOPAC.
The other components of the suite are
-
CLUSPAC for
cluster analysis
-
IMPAC for digital-image segmentation.
Created 1999: Dec 13
Latest update: 2003: Jul 19