Package index • PEcAnRTM

All functions

EDR(): ED radiative transfer module (EDR) wrapper function

EDR.preprocess.history(): Preprocess history file for EDR

burnin.thin(): Burn-in and thinning of MCMC samples

cbind(<spectra>): Combine spectra by wavelength

check.convergence(): Check convergence of multiple MCMC chains

default.settings.prospect: Defult inversion settings for PROSPECT 5 models

defparam(): Get default parameters

dtnorm(): Truncated normal distribution density

fortran_data_module(): List to FORTRAN data module

foursail(): SAIL model

generalized_plate_model(): Generalized plate model

generate.noise(): Generate autocorrelated spectral noise

get.EDR.output(): Read EDR output

invert.auto(): Inversion with automatic convergence checking

invert.custom(): Bayesian inversion of a model

invert.lsq(): Least squares model inversion

invert_bt(): Perform Bayesian inversion using BayesianTools package

load.from.name(): Load object from an RData file

lognorm.mu(): Functions for default priors Lognormal mean parameters

lognorm.sigma(): Lognormal sigma parameter

matplot(): Matplot generic method

matplot(<default>): Matplot default method

matplot(<spectra>): Plot multiple spectra on same graph

neff(): Effective sample size

params.prospect4: PROSPECT 4 parameters

params.prospect5: PROSPECT 5 parameters

params.prospect5b: PROSPECT 5B parameters

params.prospectd: PROSPECT D parameters

params2edr(): Convert named parameter vector to EDR-compatible inputs

plot(<spectra>): Plot spectra vs. wavelength

print(<spectra>): Print method for spectra S3 class

print_results_summary(): Neatly print inversion results summary

prior.defaultvals.prospect(): Default prior parameters for PROSPECT models

priorfunc.prospect(): Default PROSPECT 5 prior function

pro2s(): Coupled PROSPECT-Two-stream model

pro4sail(): PRO4SAIL model

pro4saild(): PRO4SAILD model

prospect(): PROSPECT (4, 5, or 5B) model

prospect_bt_prior(): Quick BayesianTools prior creator for PROSPECT model

read.rsr.folder(): Read and process RSR data from directory

resample(): Resample vector, matrix, or spectra

rsr.from.fwhm(): Generate relative spectral response (RSR) matrix based on FWHM data

rtm_loglike(): Generic log-likelihood generator for RTMs

rtnorm(): Random sampling from one-sided truncated normal distribution

sensor.list: Sensor spectral response functions

sensor.proper: Sensor list with proper names

setup_edr(): Setup EDR run

spectra() is_spectra(): Spectra S3 class

spectral.response(): Convolution of spectra to sensor RSR

str(<spectra>): Structure of spectra object

`[`(<spectra>): Select spectra

`[[`(<spectra>): Select spectra by wavelength

`[[<-`(<spectra>): Assign values to spectra by wavelength

summary_mvnorm(): Multivariate normal fit

summary_simple(): Simple summary statistics on MCMC samples

trim.rsr(): Trim RSR matrix to wavelength limits

wavelengths(): Retrieve wavelengths from spectra object