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unmarked (version 1.5.2)

Models for Data from Unmarked Animals

Description

Fits hierarchical models of animal abundance and occurrence to data collected using survey methods such as point counts, site occupancy sampling, distance sampling, removal sampling, and double observer sampling. Parameters governing the state and observation processes can be modeled as functions of covariates. References: Kellner et al. (2023) , Fiske and Chandler (2011) .

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Version

Install

install.packages('unmarked')

Monthly Downloads

6,898

Version

1.5.2

License

GPL (>= 3)

Homepage

https://groups.google.com/d/forum/unmarked

Maintainer

Ken Kellner

Last Published

August 20th, 2026

Functions in unmarked (1.5.2)

Swiss landscape data

Compute Sum of Squared Residuals for a Model Fit.

BBS Point Count and Occurrence Data from 2 Bird Species

Methods for Function coef in Package `unmarked'

backTransform-methods

Methods for Function backTransform in Package `unmarked'

Extract Best Unbiased Predictors (BUPs) of latent variables from ranef output

Fit the dynamic occupancy model of MacKenzie et. al (2003)

Fit the integrated distance sampling model of Kery et al. (2022).

Occupancy data for coyote, red fox, and bobcat

Methods for Function SE in Package `unmarked'

Distance-sampling detection functions and associated density functions

Cross-validation methods for fitted unmarked models and fit lists

confint-methods

Methods for Function confint in Package `unmarked'

Detection/non-detection data on the European crossbill (Loxia curvirostra)

Open population model for distance sampling data

Fit the hierarchical distance sampling model of Royle et al. (2004)

Convert .CSV File to an unmarkedFrame

computeMPLElambda

Compute the penalty weight for the MPLE penalized likelihood method

Methods for bracket extraction [ in Package `unmarked'

Landscape data for Santa Cruz Island

Create unmarkedMultFrame from Long Format Data Frame

Create a list of fitted unmarked models

Convert between wide and long data formats.

Calculate fitted (expected) values from a model

Fit the combined distance and removal model of Amundson et al. (2014).

Bin distance data

Methods for Function getFP in Package `unmarked'

Fit the generalized distance sampling model of Chandler et al. (2011).

2001 Delaware North American Amphibian Monitoring Program Data

Methods for Function getB in Package `unmarked'

Green frog count index data

Get detection probability matrix from a fitted model

Convert Poisson mean (lambda) to probability of occurrence (psi).

Fit the multi-scale occupancy model of Nichols et al. (2008)

European Jay data from the Swiss Breeding Bird Survey 2002

Generalized binomial N-mixture model for repeated count data

Generalized multinomial N-mixture model

Distance-sampling data for the Island Scrub Jay (Aphelocoma insularis)

linearComb-methods

Methods for Function linearComb in Package `unmarked'

Get order of starting values for an unmarked model

Multinomial-Poisson Mixtures Model

Model selection on a list of unmarked model fits

Create functions to compute multinomial cell probabilities

Fit the MacKenzie et al. (2002) Occupancy Model

Open population multinomial N-mixture model

Get non-parametric bootstrap samples from an unmarked model

Simulated line transect data

Fit the N-mixture Time-to-detection Model of Strebel et al. (2021)

Mallard count data

Massachusetts North American Amphibian Monitoring Program Data

Fit the MacKenzie et al. (2002) Occupancy Model with the penalized likelihood methods of Hutchinson et al. (2015) using cross-validation

Fit the occupancy model using count data

Fit a community occupancy model with species-level random effects

optimizePenalty-methods

Identify Optimal Penalty Parameter Value

Fit the occupancy model of Royle and Nichols (2003)

Fit Single-Season and Dynamic Time-to-detection Occupancy Models

Fit the multi-species occupancy model of Rota et al. (2016)

Fit the MacKenzie et al. (2002) Occupancy Model with the penalized likelihood methods of Hutchinson et al. (2015)

Fit Multi-State Occupancy Models (Nichols et al. 2007, MacKenzie et al. 2009)

Fit occupancy models when false positive detections occur (e.g., Royle and Link [2006] and Miller et al. [2011])

posteriorSamples

Draw samples from the posterior predictive distribution

Removal data for the Ovenbird

Compute multinomial cell probabilities

Parametric bootstrap for unmarked models

Plot marginal effects of covariates in unmarked models

Fit spatial hierarchical distance sampling model.

Conduct a power analysis for an unmarked model

Simulated point-transect data

Fit the N-mixture model of Royle (2004)

Fit the open N-mixture models of Dail and Madsen (2011) and Hostetler and Chandler (2015)

Estimate posterior distributions of site richness

unmarkedEstimate-class

Class "unmarkedEstimate"

Calculate residuals from a model

Extract estimates of random effect standard deviations

Extract estimates of random effect terms

Launch a Shiny app to help with power analysis

Predict from fitted models and other unmarked objects

Simulate datasets from any unmarked model type

Estimate posterior distributions of latent occupancy or abundance

unmarked-package

Models for Data from Unmarked Animals

unmarkedFrameDSO

Create an object of class unmarkedFrameDSO that contains data used by distsampOpen.

unmarkedFrameGDR

Organize data for the combined distance and removal point-count model of Amundson et al. (2014) fit by gdistremoval

unmarkedFrameMPois

Organize data for the multinomial-Poisson mixture model of Royle (2004) fit by multinomPois

unmarkedFrame-class

Class "unmarkedFrame"

unmarkedFrameMMO

Create an object of class unmarkedFrameMMO that contains data used by multmixOpen.

unmarkedFrameDS

Organize data for the distance sampling model of Royle et al. (2004) fit by distsamp

Create an unmarkedFrame, or one of its child classes.

unmarkedEstimateList-class

Class "unmarkedEstimateList"

unmarkedFit-class

Class "unmarkedFit"

unmarkedFitList-class

Class "unmarkedFitList"

unmarkedFrameOccuTTD

Create an unmarkedFrameOccuTTD object for the time-to-detection model fit by occuTTD

unmarkedFrameOccuMS

Organize data for the multi-state occupancy model fit by occuMS

unmarkedFramePCO

Create an object of class unmarkedFramePCO that contains data used by pcountOpen.

unmarkedFramePCount

Organize data for the N-mixture model fit by pcount

unmarkedFrameOccuCOP

Organize data for the occupancy model using count data fit by occuCOP

unmarkedFrameOccuComm

Organize data for the community occupancy model fit by occuComm

unmarkedModSel-class

unmarkedModSel class and methods

unmarkedFrameOccu

Organize data for the single season occupancy models fit by occu and occuRN

unmarkedFrameOccuMulti

Organize data for the multispecies occupancy model fit by occuMulti

unmarkedFrameOccuFP

Organize data for the single season occupancy models fit by occuFP

unmarkedPowerList

Summarize a series of unmarked power analyses

unmarkedRanef-class

Class "unmarkedRanef"

unmarkedMultFrame

Create an unmarkedMultFrame, unmarkedFrameGMM, unmarkedFrameGDS, or unmarkedFrameGPC object

Compute Variance Inflation Factors for an unmarkedFit Object.

unmarkedPower-methods

Methods for unmarkedPower objects

Methods for Function vcov in Package `unmarked'