hierarchicalDS: Functions For Performing Hierarchical Analysis of Distance Sampling Data

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Functions for performing hierarchical analysis of distance sampling data, with ability to use an areal spatial ICAR model on top of user supplied covariates to get at variation in abundance intensity. The detection model can be specified as a function of observer and individual covariates, where a parametric model is supposed for the population level distribution of covariate values. The model uses data augmentation and a reversible jump MCMC algorithm to sample animals that were never observed. Also included is the ability to include point independence (increasing correlation multiple observer's observations as a function of distance, with independence assumed for distance=0 or first distance bin), as well as the ability to model species misclassification rates using a multinomial logit formulation on data from double observers. New in version 2.1 is the ability to include zero inflation, but this is only recommended for cases where sample sizes and spatial coverage of the survey are high.

Author
P.B. Conn \email{paul.conn@@noaa.gov}
Date of publication
2014-11-26 08:09:54
Maintainer
Paul B Conn <paul.conn@noaa.gov>
License
Unlimited
Version
2.9

View on CRAN

Man pages

calc_linex_a
estimate optimal 'a' parameter for linex loss function
convert.HDS.to.mcmc
function to convert HierarchicalDS MCMC list vector (used in...
generate_inits
generate initial values for MCMC chain if not already...
generate_inits_misID
generate initial values for misID model if not already...
get_confusion_array
Fill confusion array - one confusion matrix for each...
get_confusion_mat
Fill a list with confusion matrices for each record
get_mod_matrix
function to produce a design matrix given a dataset and...
hierarchical_DS
Primary function for hierarchical, areal analysis of distance...
linear_adj
Produce an adjacency matrix for a vector
log_lambda_gradient
compute the first derivative of log_lambda likelihood...
log_lambda_log_likelihood
compute the likelihood for nu parameters
mcmc_ds
Function for MCMC analysis
plot_N_map
function to plot a map of abundance. this was developed for...
plot_obs_pred
plot 'observed' versus predicted values for abundance of each...
post_loss
function to calculate posterior predictive loss given the...
probit.fct
Mrds probit detection and related functions
rect_adj
Produce an RW1 adjacency matrix for a rectangular grid for...
rect_adj_RW2
Produce an RW2 Adjacency matrix for a rectangular grid for...
rrw
SIMULATE AN ICAR PROCESS
simdata
MCMC output from running example in Hierarchical DS
sim_out
MCMC output from running example in Hierarchical DS
simulate_data
function to simulate double observer spatial distance...
square_adj
Produce an adjacency matrix for a square grid
stack_data
function to stack data (going from three dimensional array to...
stack_data_misID
function to stack data for midID updates (going from four...
summary_N
calculate parameter estimates and confidence intervals for...
switch_pdf
function to calculate the joint pdf for a sample of values...
switch_sample
function to sample from a specified probability density...
switch_sample_prior
function to sample from hyperpriors of a specified...
table.mcmc
function to export posterior summaries from an mcmc object to...

Files in this package

hierarchicalDS
hierarchicalDS/inst
hierarchicalDS/inst/cache
hierarchicalDS/inst/cache/cache-example11_dec9ea02145bf8c1095cf437a7785a4c.rdx
hierarchicalDS/inst/cache/cache-example7_1640587fd6f8e638b98c524b7123ab4b.RData
hierarchicalDS/inst/cache/cache-example8_d1e3bea60985f9d4426852c68af6d816.RData
hierarchicalDS/inst/cache/cache-example10_522be745bfde15eff1594dca0074fd64.RData
hierarchicalDS/inst/cache/cache-example4_b43fe5abd76a24257f2f78e4bc001b2b.RData
hierarchicalDS/inst/cache/cache-example6_88ab8a01ed70b5e42b8b3dd01ef497ee.rdx
hierarchicalDS/inst/cache/cache-example20_6f7447e99b705f65de93e63e193f819f.RData
hierarchicalDS/inst/cache/cache-example14_6700128c3164be34d9c445284c7ce74e.rdb
hierarchicalDS/inst/cache/cache-example21_ce2624066512c74c285f03af2512a639.rdb
hierarchicalDS/inst/cache/cache-install2_ad7f9b4fa93b009394879a017973668b.rdx
hierarchicalDS/inst/cache/cache-example13_042a549245272ed844ac6b568a2a2cb5.rdx
hierarchicalDS/inst/cache/cache-example10_522be745bfde15eff1594dca0074fd64.rdx
hierarchicalDS/inst/cache/cache-example16_dce2cf83f0ab177834e256535325e427.rdb
hierarchicalDS/inst/cache/cache-example15_86d12bb607e1490926b5e0f1d0649b3e.rdb
hierarchicalDS/inst/cache/cache-example21_ce2624066512c74c285f03af2512a639.rdx
hierarchicalDS/inst/cache/cache-example5_08fd60505630e091a5ab43cdd20103f2.RData
hierarchicalDS/inst/cache/cache-example12_6e95c814fb486629588b6c7248a9631b.RData
hierarchicalDS/inst/cache/cache-example15_86d12bb607e1490926b5e0f1d0649b3e.rdx
hierarchicalDS/inst/cache/cache-example13_042a549245272ed844ac6b568a2a2cb5.rdb
hierarchicalDS/inst/cache/cache-example3_1a5d77ae6c4e263618c484339a31040c.rdb
hierarchicalDS/inst/cache/cache-example13_042a549245272ed844ac6b568a2a2cb5.RData
hierarchicalDS/inst/cache/cache-example17_5dea3befa2f5a8c4ff414568f703d3ef.rdx
hierarchicalDS/inst/cache/cache-install1_495d4a18e95bbe663768664c96919772.RData
hierarchicalDS/inst/cache/cache-example11_dec9ea02145bf8c1095cf437a7785a4c.RData
hierarchicalDS/inst/cache/cache-example5_08fd60505630e091a5ab43cdd20103f2.rdx
hierarchicalDS/inst/cache/cache-example4_b43fe5abd76a24257f2f78e4bc001b2b.rdb
hierarchicalDS/inst/cache/cache-example8_d1e3bea60985f9d4426852c68af6d816.rdb
hierarchicalDS/inst/cache/cache-example20_6f7447e99b705f65de93e63e193f819f.rdx
hierarchicalDS/inst/cache/cache-example2_1843aba5a766a84a0a6d376186282424.rdb
hierarchicalDS/inst/cache/cache-example14_6700128c3164be34d9c445284c7ce74e.RData
hierarchicalDS/inst/cache/cache-example18_35bc47a2091aebf483f6a43b0fd9d253.rdb
hierarchicalDS/inst/cache/cache-example17_5dea3befa2f5a8c4ff414568f703d3ef.rdb
hierarchicalDS/inst/cache/cache-example6_88ab8a01ed70b5e42b8b3dd01ef497ee.rdb
hierarchicalDS/inst/cache/cache-example3_1a5d77ae6c4e263618c484339a31040c.rdx
hierarchicalDS/inst/cache/cache-example5_08fd60505630e091a5ab43cdd20103f2.rdb
hierarchicalDS/inst/cache/cache-example18_35bc47a2091aebf483f6a43b0fd9d253.rdx
hierarchicalDS/inst/cache/cache-install2_ad7f9b4fa93b009394879a017973668b.RData
hierarchicalDS/inst/cache/cache-example10_522be745bfde15eff1594dca0074fd64.rdb
hierarchicalDS/inst/cache/cache-example22_26009984fc3c8c17d6aea2fcf9799aa0.rdx
hierarchicalDS/inst/cache/cache-example2_1843aba5a766a84a0a6d376186282424.RData
hierarchicalDS/inst/cache/cache-install1_495d4a18e95bbe663768664c96919772.rdx
hierarchicalDS/inst/cache/cache-example16_dce2cf83f0ab177834e256535325e427.rdx
hierarchicalDS/inst/cache/cache-example19_e27b6f11e2391ff1df05057eac8c0fa5.rdb
hierarchicalDS/inst/cache/cache-example1_82a67210abcd15ccfdb62ae5d45a6c9d.rdb
hierarchicalDS/inst/cache/cache-example17_5dea3befa2f5a8c4ff414568f703d3ef.RData
hierarchicalDS/inst/cache/cache-example7_1640587fd6f8e638b98c524b7123ab4b.rdb
hierarchicalDS/inst/cache/cache-example19_e27b6f11e2391ff1df05057eac8c0fa5.rdx
hierarchicalDS/inst/cache/cache-example11_dec9ea02145bf8c1095cf437a7785a4c.rdb
hierarchicalDS/inst/cache/cache-example2_1843aba5a766a84a0a6d376186282424.rdx
hierarchicalDS/inst/cache/cache-example12_6e95c814fb486629588b6c7248a9631b.rdx
hierarchicalDS/inst/cache/cache-example9_dd16693b1903f69e47e937a065112f2d.RData
hierarchicalDS/inst/cache/cache-example1_82a67210abcd15ccfdb62ae5d45a6c9d.RData
hierarchicalDS/inst/cache/cache-example18_35bc47a2091aebf483f6a43b0fd9d253.RData
hierarchicalDS/inst/cache/cache-example9_dd16693b1903f69e47e937a065112f2d.rdb
hierarchicalDS/inst/cache/cache-example9_dd16693b1903f69e47e937a065112f2d.rdx
hierarchicalDS/inst/cache/cache-example20_6f7447e99b705f65de93e63e193f819f.rdb
hierarchicalDS/inst/cache/cache-example7_1640587fd6f8e638b98c524b7123ab4b.rdx
hierarchicalDS/inst/cache/cache-example15_86d12bb607e1490926b5e0f1d0649b3e.RData
hierarchicalDS/inst/cache/cache-install1_495d4a18e95bbe663768664c96919772.rdb
hierarchicalDS/inst/cache/cache-example16_dce2cf83f0ab177834e256535325e427.RData
hierarchicalDS/inst/cache/cache-example19_e27b6f11e2391ff1df05057eac8c0fa5.RData
hierarchicalDS/inst/cache/cache-example4_b43fe5abd76a24257f2f78e4bc001b2b.rdx
hierarchicalDS/inst/cache/cache-example12_6e95c814fb486629588b6c7248a9631b.rdb
hierarchicalDS/inst/cache/cache-__packages
hierarchicalDS/inst/cache/cache-example3_1a5d77ae6c4e263618c484339a31040c.RData
hierarchicalDS/inst/cache/cache-example22_26009984fc3c8c17d6aea2fcf9799aa0.RData
hierarchicalDS/inst/cache/cache-example6_88ab8a01ed70b5e42b8b3dd01ef497ee.RData
hierarchicalDS/inst/cache/cache-example21_ce2624066512c74c285f03af2512a639.RData
hierarchicalDS/inst/cache/cache-example1_82a67210abcd15ccfdb62ae5d45a6c9d.rdx
hierarchicalDS/inst/cache/cache-example8_d1e3bea60985f9d4426852c68af6d816.rdx
hierarchicalDS/inst/cache/cache-example14_6700128c3164be34d9c445284c7ce74e.rdx
hierarchicalDS/inst/cache/cache-example22_26009984fc3c8c17d6aea2fcf9799aa0.rdb
hierarchicalDS/inst/cache/cache-install2_ad7f9b4fa93b009394879a017973668b.rdb
hierarchicalDS/inst/HierarchicalDS_vignette.Rnw
hierarchicalDS/inst/HierarchicalDS_vignette.tex
hierarchicalDS/inst/HierarchicalDS_vignette.toc
hierarchicalDS/inst/NEWS.txt
hierarchicalDS/inst/figure
hierarchicalDS/inst/figure/graphics-example22.png
hierarchicalDS/inst/HierarchicalDS_vignette.pdf
hierarchicalDS/inst/HierarchicalDS_vignette.log
hierarchicalDS/inst/simulate_data_overd.R
hierarchicalDS/NAMESPACE
hierarchicalDS/data
hierarchicalDS/data/simdata.rda
hierarchicalDS/data/sim_out.rda
hierarchicalDS/data/datalist
hierarchicalDS/data/simdata.rdata
hierarchicalDS/R
hierarchicalDS/R/simulate_data.R
hierarchicalDS/R/spat_funcs.R
hierarchicalDS/R/mcmc_ds.R
hierarchicalDS/R/hierarchical_DS.R
hierarchicalDS/MD5
hierarchicalDS/DESCRIPTION
hierarchicalDS/man
hierarchicalDS/man/plot_obs_pred.Rd
hierarchicalDS/man/rect_adj.Rd
hierarchicalDS/man/square_adj.Rd
hierarchicalDS/man/rrw.Rd
hierarchicalDS/man/post_loss.Rd
hierarchicalDS/man/hierarchical_DS.Rd
hierarchicalDS/man/switch_sample_prior.Rd
hierarchicalDS/man/get_mod_matrix.Rd
hierarchicalDS/man/linear_adj.Rd
hierarchicalDS/man/sim_out.Rd
hierarchicalDS/man/generate_inits_misID.Rd
hierarchicalDS/man/stack_data_misID.Rd
hierarchicalDS/man/log_lambda_gradient.Rd
hierarchicalDS/man/log_lambda_log_likelihood.Rd
hierarchicalDS/man/convert.HDS.to.mcmc.Rd
hierarchicalDS/man/get_confusion_array.Rd
hierarchicalDS/man/switch_pdf.Rd
hierarchicalDS/man/switch_sample.Rd
hierarchicalDS/man/calc_linex_a.Rd
hierarchicalDS/man/probit.fct.Rd
hierarchicalDS/man/rect_adj_RW2.Rd
hierarchicalDS/man/simdata.Rd
hierarchicalDS/man/stack_data.Rd
hierarchicalDS/man/generate_inits.Rd
hierarchicalDS/man/simulate_data.Rd
hierarchicalDS/man/get_confusion_mat.Rd
hierarchicalDS/man/table.mcmc.Rd
hierarchicalDS/man/summary_N.Rd
hierarchicalDS/man/mcmc_ds.Rd
hierarchicalDS/man/plot_N_map.Rd