Benchmarks
Here are some standard benchmark
datasets and models for testing the accuracy of TSP. For an updated
and expanded set of benchmarks, please see this page: http://www.stanford.edu/~clint/bench
, which includes a high accuracy Klein-I FIML benchmark, more AR(1) benchmarks,
many ARIMA models (exact ML), GARCH(1,1), Probit, Logit, Poisson, Negative
Binomial, Ordered Probit.
- Longley,
JASA (1967) -- linear regression
- Grunfeld
investment data -- analyzed in Theil (1971)
- grunsur.tsp computes the following:
- OLS
- SUR
- Seemingly Unrelated Regressions
- iterated
SUR
- (iterated)
SUR with cross-equation constraints
- Bartlett pears data
-- analyzed by Hildreth and Lu, and by Henshaw
- pears.tsp computes the following:
- OLS
- Durbin-Watson
statistic and its exact P-value
- AR(1)
conditional ML via grid search (Hildreth-Lu)
- AR(1)
conditional ML via full iteration (Cochran-Orcutt)
- AR(1)
exact ML via full iteration (Beach-MacKinnon)
- Wilkinson's
"Statistics Quiz"
- National
Institutes of Standards and Technology (NIST) "Statistical Reference
Datasets"
- NIST StRD web page - contains many test problems and
certified results for univariate statistics, anova, linear regression,
and nonlinear regression.
- Univariate
statistics
- Table of results for Sun 4 TSP obtains at least 8
correct digits for mean, standard deviation, and first order
autocorrelation for 7 data series.
- uni.tsp Code to run 7 series
- ANOVA
- Ordinary
Least Squares
- Nonlinear
Least Squares
If you have any questions
or comments about TSP please send an email to info@tspintl.com.
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