Compute house price indexes and series using a variety of different methods and
models common through the real estate literature.  Evaluate index 'goodness' based
on accuracy, volatility and revision statistics. Background on basic model construction
for repeat sales models can be found at: Case and Quigley (1991)
<https://www.jstor.org/stable/2109686> and for hedonic pricing models at:
Bourassa et al (2006) <doi:10.1016/j.jhe.2006.03.001>. The package author's working paper on the
random forest approach to house price indexes can be found at: <http://www.github.com/andykrause/hpi_research>.
dplyr, magrittr, lubridate, robustbase, ggplot2, imputeTS (>=
3.0), purrr, forecast, caret, gridExtra, MASS, rlang, plyr,
zoo, ranger, pdp

Compute house price indexes and series using a variety of different methods and
models common through the real estate literature.  Evaluate index 'goodness' based
on accuracy, volatility and revision statistics. Background on basic model construction
for repeat sales models can be found at: Case and Quigley (1991)
<https://ideas.repec.org/a/tpr/restat/v73y1991i1p50-58.html> and for hedonic pricing models at:
Bourassa et al (2006) <doi:10.1016/j.jhe.2006.03.001>. The package author's working paper on the
random forest approach to house price indexes can be found at: <http://www.github.com/andykrause/hpi_research>.
dplyr, magrittr, lubridate, robustbase, ggplot2, imputeTS (>=
3.0), purrr, forecast, gridExtra, MASS, rlang, plyr, zoo,
ranger, pdp

Functions to plot graphviz style graphs of sets of HPO terms
Functions for visualising a set of HPO-encoded phenotypes in a variety of ways
R (>= 2.10), Rgraphviz, functional, plotrix, Hmisc

Collection of functions for manipulating sets of HPO terms and plotting them with a various options

Collection of functions for manipulating sets of HPO terms and plotting them with a various options.

Collection of functions for manipulating sets of HPO terms and
plotting them with a various options.

hpower
0.1-0
25 November 1991
Written by Daniel F. Heitjan (dheitjan@peter.cpmc.columbia.edu).
R port by Stefan Funke (funke@attglobal.net)
Computation of power and sample size for tests of the general
linear hypothesis
A suite of Splus/R functions to compute power and sample
size for tests of the general linear hypothesis.
These functions are not copyrighted.  The author requests,
however, that you acknowledge the source and communicate any
improvements to him.  No guarantees WHATSOEVER from the author or the
porter.