This package contains functions for paleolimnology -
wa-regression (see also package analogue by G. Simpson!),
wa-pls and the mowing-window approch. The function palplot
allows a first plot of the data including a trend analysis. The
pom function is just a first test version.
Fri Jun 26 08:48:47 2009; botanikschule-B

Thu Jul 9 09:20:25 2009; botanikschule-B

This package contains functions for paleolimnology -
wa-regression (see also package analogue by G. Simpson!),
wa-pls and the mowing-window approch. The function palplot
allows a first plot of the data including a trend analysis. The
mtf function is just a first test version.

Principal Axes Methods for Contingency Tables with Partition
Structures on Rows and Columns
Correspondence Analysis of Contingency Tables with Simple
and Double Structures Superimposed Representations, Intra
Blocks Internal Corresponde Analysis, MFACT-DP.

Correspondence Analysis of Contingency Tables with Simple
and Double Structures Superimposed Representations, Intra
Blocks Corresponde Analysis (IBCA), Weighted Intra Blocks
Corresponde Analysis (WIBCA).

Correspondence Analysis of Contingency Tables with Simple
and Double Structures Superimposed Representations, Intra
Blocks Correspondence Analysis (IBCA), Weighted Intra Blocks
Correspondence Analysis (WIBCA).

Power analysis for random effects in mixed models
Simulation functions to assess or explore the power of a
dataset to estimates significant random effects (intercept or
slope) in a mixed model. The functions are based on the "lme4"
package.

Power Analysis for Random Effects in Mixed Models
person("Julien","Martin", email = "julienmartin@abdn.ac.uk",
role = c("aut", "cre"))
Simulation functions to assess or explore the power of a dataset to estimates significant random effects (intercept or slope) in a mixed model. The functions are based on the "lme4" package.
lmerTest, gmodels, lattice, mvtnorm, lme4

person("Julien","Martin", email = "julien.martin@uottawa.ca",
role = c("aut", "cre"))
Simulation functions to assess or explore the power of a dataset to estimates significant random effects (intercept or slope) in a mixed model. The functions are based on the "lme4" and "lmerTest" packages.