Estimators for Two-Sample Capture-Recapture Studies

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Documentation for package ‘Petersen’ version 2023.12.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

cap_hist_to_n_m_u	Convert capture history data to n, m and u for use in BTSPAS
data_btspas_diag1	Estimating abundance of outgoing smolt - BTSPAS - diagonal case
data_btspas_nondiag1	Estimating abundance of salmon - BTSPAS - non-diagonal case
data_kokanee_tagloss	Capture-recapture on Kokanee in Metolius River with tag loss
data_NorthernPike	Capture-recapture experiment on Northern Pike in Mille Lacs, MN, in 2005.
data_NorthernPike_tagloss	Capture-recapture experiment on Northern Pike in Mille Lacs, MN, in 2005 with tagloss information.
data_rodli	Capture-recapture experiment at Rodli Tarn.
data_sim_reward	Simulated data for reward tags used to estimate reporting rate
data_sim_tagloss_t2perm	Simulated data for tag loss with second permanent tag.
data_sim_tagloss_twoD	Simulated data for tag loss with 2 distinguishable tags.
data_spas_harrison	Estimating abundance of salmon - SPAS - Harrison River
data_wae_is_long	Walleye data with incomplete stratification with length covariate
data_wae_is_short	Walleye data with incomplete stratification with no covariates and condensed
data_yukon_reverse	Yukon River data used for Reverse Capture-Recapture example.
expit	Logit and anti-logit function.
fit_classes	*LP_fit*, *LP_IS_fit*, *LP_SPAS_cit*, *CL_fit*, *LP_BTSPAS_fit_Diag*, *LP_BTSPAS_fit_NonDiag*, *LP_CL_fit* classes.
logit	Logit and anti-logit function.
LP_AICc	Create an AIC table comparing multiple LP fits
LP_BTSPAS_est	Extract estimates of abundance after BTSPAS fit
LP_BTSPAS_fit_Diag	Wrapper (*_fit) to call the Time Stratified Petersen Estimator with Diagonal Entries function in BTSPAS.
LP_BTSPAS_fit_NonDiag	Wrapper (*_fit) to call the Time Stratified Petersen Estimator with NON-Diagonal Entries function in BTSPAS.
LP_CL_fit	Fit the Chen-Lloyd model to estimate abundance using a non-parametric smoother for a covariates
LP_est	Estimate abundance after the LP conditional likelihood fit.
LP_est_adjust	Estimate abundance after empirical adjustments for various factors.
LP_fit	Fit a Lincoln-Petersen Model using conditional likelihood
LP_IS_est	Estimate abundance after the LP_IS conditional likelihood fit.
LP_IS_fit	Fit a Lincoln-Petersen Model with incomplete stratification
LP_IS_print	Print the results from a fit a Lincoln-Petersen Model with incomplete stratification
LP_modavg	Create an table of individual estimates and the model averaged values
LP_SPAS_est	Extract estimates of abundance after SPAS fit
LP_SPAS_fit	Fit a Stratified-Petersen SPAS model.
LP_summary_stats	Compute summary statistics from the capture histories
LP_test_equal_mf	Test for equal marked fractions in LP experiment
LP_test_equal_recap	Test for equal recapture probability in LP experiment
LP_TL_est	Estimate abundance after the LP_TL (tag loss) conditional likelihood fit.
LP_TL_fit	Fit a Lincoln-Petersen Model with Tag Loss using conditional likelihood
LP_TL_simulate	Simulate data from a Lincoln-Petersen Model with Tag Loss
split_cap_hist	Split a vector of capture histories into a matrix with one column for each occasion