library(alm)
Remember to get your api key, pass it in in the key parameter. Notice that we are passing the base url for the Crossref API, whereas the default is for the PLOS url http://alm.plos.org/api/v3/articles
# install the experimental parallel branch | |
# remotes::install_github("zoonproject/zoon@parallel") | |
library (zoon) | |
# example workflow for 4 independent models that may take a while to run | |
run_wf <- function () { | |
workflow(occurrence = UKAnophelesPlumbeus, | |
covariate = UKBioclim, | |
process = Replicate(Background(n = 1000), 4), | |
model = GBM(max.trees = 10000), |
# require(devtools) | |
# install_github('SevillaR/Andaclima') | |
require(Andaclima) | |
rm(list = ls()) | |
stations <- getAndalusia_ACS() | |
metainfo <- getMetaData(provincia = stations$province.code, | |
estacion = stations$station.code , |
# Author: Joona Lehtomäki <joona.lehtomaki@gmail.com> | |
# Updated: 13.11.2011 | |
# Version: 0.0.1 | |
if (!require("rgdal")) { | |
install.packages("rgdal") | |
} | |
if (!require("raster")) { | |
install.packages("raster") |
--- | |
title: "Untitled" | |
author: "Jeff W. Hollister" | |
date: "2/2/2016" | |
output: beamer_presentation | |
--- | |
```{r setup, include=FALSE} | |
knitr::opts_chunk$set(echo = FALSE) |
install.packages('zoon') | |
library(zoon) | |
vignette('Building_a_module') | |
############# | |
## Simples ## | |
############# |
#Title: An example of the correlation of x and y for various distributions of (x,y) pairs | |
#Tags: Mathematics; Statistics; Correlation | |
#Author: Denis Boigelot | |
#Packets needed : mvtnorm (rmvnorm), #RSVGTipsDevice (devSVGTips) | |
#How to use: output() | |
# | |
#This is an translated version in R of an Matematica 6 code by Imagecreator. | |
# from http://en.wikipedia.org/wiki/File:Correlation_examples2.svg | |
library(mvtnorm) |
Which documents belong to each topic? | |
Documents don't belong to a single topic, there is a distribution of topics | |
over each document. | |
But we can Find the topic with the highest proportion for each document. | |
That top-ranking topic might be called the 'topic' for the document, but note | |
that all docs have all topics to varying proportions | |
Assume that we start with `topic_docs` from the output of the mallet package |