Package: pla
Type: Package
Title: Parallel Line Assays
Version: 0.2
Date: 2015-09-09
Author: Jens Henrik Badsberg
Depends: R (>= 3.1.0), methods
Maintainer: Jens Henrik Badsberg <pla2015@badsberg.eu>
Description: Parallel Line Assays: Completely randomized design,
Randomized Block design, and Latin squares design.
Balanced data are fitted as described in the Ph.Eur.
In the presence of missing values complete data analysis can be
performed (with computation of Fieller's confidence intervals for
the estimated potency), or imputation of values can be applied.
The package contains a script such that a pdf-document with a
report of an analysis of an assay can be produced from an input file
with data of the assay. Here no knowledge of R is needed by the user.
License: GPL (>= 2)
Packaged: 2015-09-09 17:00:50 UTC; Jens Henrik
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2015-09-09 21:19:32

Title: A Pairwise Likelihood Augmented Cox Estimator for Left-Truncated
Authors@R: person("Fan", "Wu", email = "fannwu@umich.edu",
Description: A semi-parametric estimation method for the Cox model
with left-truncated data using augmented information

Title: Tools for Accessing the Google Maps API
Description: The main functions in this package are drive_time
(used for calculating distances between physical addresses or coordinates) and
geocode_url (used for estimating the lat/long coordinates
of a physical address). Optionally, it generates the cryptographic signatures necessary
for making API calls with a Google for Work/Premium account within the geocoding process.
These accounts have larger quota limits than the "standard_api" and, thus, this package
may be useful for individuals seeking to submit large batch jobs within R to the Google Maps API.
Placement also provides methods for accessing the standard API using a (free) Google API key
Imports: RCurl, jsonlite, base64enc, digest, urltools, stringi

Title: PLastic ACcumulation Estimate using R (PLACER)
person("Davi", "Castro-Tavares", email = "davi.tavares@leibniz-zmt.de",
role = c("cre","aut")), person("Esteban", "Acevedo-Trejos",
email = "esteban.acevedo@leibniz-zmt.de", role = c("aut")),
email = "jailsonfm@gmail.com", role = c("aut")) )
Description: Assessment of the prevalence of plastic
debris in bird nests based on bootstrap replicates. The package allows for
calculating bootstrapped 95% confidence intervals for the estimated prevalence
of debris. Combined with a Bayesian approach, the resampling simulations can
be also used to define appropriate sample sizes to detect prevalence of plastics.
The method has wide application, and can also be applied to estimate confidence
intervals and define sample sizes for the prevalence of plastics ingested by any
other organisms. The method is described in Tavares et al. (Submitted).
Suggests: dplyr, knitr, rmarkdown, kableExtra