Packaged: Thu Jul 28 22:29:37 2005; braun

Description: These data sets are taken from the book Introduction to
Linear Regression Analysis (3rd ed), by the above authors.

Description: Most of this package consists of data sets from the
to Linear Regression Analysis (3rd ed), by Montgomery et al.
Some additional data sets and functions useful in an

undergraduate regression course are included.

Title: Data Sets from Montgomery, Peck and Vining
to Linear Regression Analysis (3rd ed), by Montgomery, Peck
Some additional data sets and functions are included.

Some additional data sets and functions related to visualization
of linear and nonparametric regression results are included.

Some additional data sets and functions are also included.
Depends: R (>= 2.0.1), lattice, KernSmooth

Title: Calculations of One Discrete Model in Several Time Steps
Suggests: knitr, rmarkdown, matrixcalc, markovchain, matlib
Description: A matrix discrete model having the form
The calculation of the values of 'M[i]' only for
pre-selected values of 'i'. The method of calculation
is presented in the vignette 'Fundament' ('Base'). Maybe it`s own
idea of the author of the package. A weakness is that the method
gives information only in selected steps of the process.
It mainly refers to cases with matrices that are not Markov chain.
If 'Q' is Markov transition matrix, then MUPkL() may be
used to calculate the steady-state distribution 'p' for
Matrix power of non integer (matrix.powerni()) gives
the same results as a mpower() from package 'matlib'.
"ON NON-INTEGER POWERS OF A SQUARE MATRIX",

Authors@R: c(person("Patrick", "Mair", role = c("aut", "cre"), email = "mair@fas.harvard.edu"))
Description: Supplementary materials and datasets for the book "Modern Psychometrics With R" (Mair, 2018, Springer useR! series).

Title: Modelling and Quantitative Methods in Fisheries
Authors@R: person("Malcolm", "Haddon", role = c("aut", "cre"),
Description: Complements the book "Using R for Modelling and
Quantitative Methods in Fisheries" ISBN: 9780367469894, being
published in June 2020 by Chapman & Hall in their "Using R series".
There are numerous functions and data-sets that are used in the