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View ncites_scholar
#' Retrieve number of citations of a paper in Google Scholar
#' This function retrieves the number of citations of a given paper in Google Scholar.
#' @param user character vector. The user ID in Google Scholar Citations. Obtain from author's profile website in google scholar (
#' @param paper character vector. The paper ID in Google Scholar Citations. Copy from publication list in author's profile website.
#' @author F. Rodriguez-Sanchez
#' @examples
#' ncites_scholar(user="B7vSqZsAAAAJ", paper="d1gkVwhDpl0C")
View PDF-2-text-or-CSV.r
# Here are a few methods for getting text from PDF files. Do read through
# the instructions carefully! NOte that this code is written for Windows 7,
# slight adjustments may be needed for other OSs
# Tell R what folder contains your 1000s of PDFs
dest <- "G:/somehere/with/many/PDFs"
# make a vector of PDF file names
myfiles <- list.files(path = dest, pattern = "pdf", full.names = TRUE)
# Joseph R. Mihaljevic
# July 2013
# (Partial) Bayesian analysis of variance, accounting for heteroscedasticity
# Generate some artificial data:
# Normally distributed groups, but heteroscedastic
a <- rnorm(25, mean=8, sd=10)
b <- rnorm(50, mean=5, sd=2)
c <- rnorm(25, mean=3, sd=.1)
d <- rnorm(25, mean=11, sd=3)
e <- rnorm(50, mean=13, sd=2)
View gdal_project.R
## Function to use GDAL to project coordinate reference system
# See for additional details
# `resampling` can be 'near' (nearest neighbour), 'bilinear', 'cubic', or
# 'lanczos' (Lanczos windowed sinc resampling).
# `extent` should be a bbox object or a vector of c(xmin, ymin, xmax, ymax)
# `of` is the output format (use GDAL short name as given by the name field of
# gdalDrivers(), or at
# `extension` is the output extension corresponding to the primary file
# `ot` is the output type (see
View calculate-cover.R
#' Calculate total cover per species in vegetation transects
#' Calculate total cover per species in each transect, layer within transect, etc.
#' Optionally, the function can also calculate length of bare ground (as ground not covered
#' by any plant species).
#' @export
#' @author F Rodriguez-Sanchez
#' @importFrom plyr ddply
#' @importFrom gtools odd even
View tables.Rmd
title: "A few methods for making tables in rmarkdown"
output: html_document
Packages that have appeared since my original look into this, and seem great:
View gistmap.geojson
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View quicktopomap.R
# Get elevation data from the internet for specified coordinates
elev <- getData("SRTM", download=T, lon=-76.6, lat=18.1)
# Specify desired extent
ext <- c(-76.68, -76.65, 18.08, 18.11)
ext2 <- c(-76.675, -76.655, 18.088, 18.10) # for plotting