Description: Tools to estimate pollinator body size and co-varying traits. This package contains novel Bayesian predictive models of pollinator body size (for bees and hoverflies) as well as preexisting predictive models for pollinator body size (currently implemented for ants, bees, butterflies, flies, moths and wasps) as well as bee tongue length and foraging distance, total field nectar loads and wing loading. An additional GitHub repository <https://github.com/liamkendall/pollimetrydata> provides model objects to use the bodysize function internally. All models are described in Kendall et al (2018) <doi:10.1101/397604>.
Packaged: 2018-11-19 01:40:57 UTC; liamkendall

Title: R client for the Huffpost Pollster API
Description: An R interface to the Huffington Post Pollster API, which provides
a programmatic interface to political polls.
Authors@R: c(person("Jeffrey B.", "Arnold", email = "jeffrey.arnold@gmail.com",
Suggests: knitr, dplyr, ggplot2, testthat

programmatic interface to political polls.

Title: Client for the HuffPost Pollster API
Description: Client for the HuffPost Pollster API, which provides
access to U.S. opinion polls since 2004.

person("Drew", "Linzer", role = c("aut")))
Suggests: knitr, dplyr, ggplot2, rmarkdown, testthat
Collate: 'pollstr-package.R' 'chart.R' 'charts.R' 'polls.R'

Imports: dplyr, httr, jsonlite, purrr, readr, stringr, tibble
Suggests: knitr, ggplot2, rmarkdown, testthat, tidyr

access to U.S. polls on elections and political opinion.
Imports: httr, lubridate, purrr, stringr
Suggests: jsonlite, knitr, readr, rmarkdown, tidyverse, xml2

Suggests: dplyr, ggplot2, jsonlite, knitr, readr, rmarkdown, tidyr

Title: Calculate Crosstab and Topline Tables of Weighted Survey Data
Maintainer: John D. Johnson <john.d.johnson@marquette.edu>
Description: Calculate common types of tables for weighted survey data.
Options include topline and (2-way and 3-way) crosstab tables of
categorical or ordinal data as well as summary tables of weighted
numeric variables. Optionally, include the margin of error at
selected confidence intervals including the design effect. The
design effect is calculated as described by
on page 257. Output takes the form of tibbles (simple data frames).
This package conveniently handles labelled data, such as that
commonly used by 'Stata' and 'SPSS.' Complex survey design is
labelled (>= 2.0.0), lubridate, forcats, rlang (>= 0.4.5)
Suggests: ggplot2 (>= 3.3.0), knitr, rmarkdown
Packaged: 2020-03-24 17:29:31 UTC; johnsonjoh