Spatially Explicit Capture-Recapture
Add Covariates to Mask or Traps
Mark-resight Data
Combine Telemetry and Detection Data
Compare SECR Models
Model Compatibility
Coerce capthist to Data Frame or Array
Coerce traps object to mask
Coerce ppp object to popn
Initial Parameter Values for SECR
Add Binned Covariate
Spatial Capture History Object
Dissect Spatial Capture History Object
Overdispersion of Activity Centres
Circular Probability
Replicate Rows
Closed population estimates
Closure tests
Detector Clustering
Coefficients of secr Object
Array of Parameter Estimates
Profile Likelihood Confidence Intervals
Contour Detection Probability
House mouse live trapping data
Covariates Attribute
Coefficient of Variation
Construct Density Design Data
Convert Data To Or From BUGS Format
Edit Mask Points
Import or export data
Derived Parameters of Fitted SECR Model
Detail Specification for secr.fit
Detection Functions
Detector Type
Deviance of fitted secr model and residual degrees of freedom
Rasterize Area Search or Transect Data
Distance To Nearest Detector
Density Surfaces
Confidence Ellipses
Empirical Variance of H-T Density Estimate
Mask Buffer Diagnostic Plot
Expected Number of Individuals
Simulated Movements
Frequently Asked Questions, And Others
Estimate overdispersion
Probability Density of Activity Centre
Activity Centres of Detected and Undetected Animals
Construct Grid Cells
Hybrid Mixture Model
First or Last Part of an Object
Home Range Statistics
Combine or Split Sessions of capthist Object
Overlap Index
Fit Multiple SECR Models
Plot Likelihood Surface
Logit Transformation
Multinomial Coefficient of SECR Likelihood
Likelihood Ratio Test
Construct capthist Object
Construct Lacework Detector Design
Build Habitat Mask
Construct Spatial Coverage Design
Construct Systematic Detector Design
Build Detector Array
Build Detector Array on Triangular or Hexagonal Grid
Create Default Design Data
Initial Parameter Values
Work with Open Population data
Mask Diagnostics
Mask Object
Methods for MCgof Objects
Monte Carlo Goodness-of-fit for SECR Models
Averaging of SECR Models Using Akaike's Information Criterion
Multi-session Objects
Non-target Data
Key to Petal Plot
Multi-core Processing
Net Detection Probability
Telemetry Fixes in Polygons
Plot Detection Histories
Plot Habitat Mask, Density or Resource Surface
Plot Population Object
Plot Detection Functions
Plot traps Object
Outline Around Mask Cells
Mixture Model Check
Points Inside Polygon
Area of Polygon(s)
Population Object
SECR Model Predictions
Predict Density Surface
Print Detections
Print or Summarise secr Object
Print Detectors
Random Landscape
Create a RasterLayer Object from Mask or Dsurface
Combine capthist Objects
Combine popn Objects
Combine traps Objects
Read Habitat Mask From File
Import Telemetry Fixes
Read Detector Data From File
Rectangular Mask
Combine Occasions Or Detectors
Combine Columns
Population Size
Convert Data to RMark Input Format
RSE from Fitted Model
Smoothed Resource Surface
Score Test for SECR Models
Defunct Functions in Package secr
Deprecated Functions in Package secr
Internal Functions
Spatially Explicit Capture--Recapture Models
Changes in secr 5.0
Construct Detection Model Design Matrices and Lookups
Spatially Explicit Capture--Recapture
Goodness-of-Fit Test
Random Number Seed
Goodness-of-fit Test Results
Session Vector
Number of Threads
Fix Inconsistent Covariates
Sighting Attributes
Signal Fields
Reformat Signal Data
Simulate Detection Histories
Simulate 2-D Population
Simulate From Fitted secr Model
Smooth Terms in SECR Models
Slice Transect Into Shorter Sections
Sort Rows of capthist or mask Object
Detector or Mask Spacing
Speed Tips
Colour Strip Legend
Subset or Split capthist Object
Subset, Split or Combine Mask Objects
Subset popn Object
Subset traps Object
Mask Buffer Width
Summarise Detections
Summarise Habitat Mask
Summarise Simulated Population
Summarise Detector Array
Time-varying Covariates
Transform Point Array
Complex Detector Layouts
Detector Array
Detector Attributes
Density Trend
Drop Unwanted List Components
Problems in Fitting SECR Models
Specifying a Dynamic Population
Update Old capthist Format
Detector Usage
Plot usage, detections or sightings.
Non-Euclidean Distances
Utility Functions
Variance - Covariance Matrix of SECR Parameters
Check SECR Data
Write Data to Text File
Upload to GPS
Functions to estimate the density and size of a spatially distributed animal population sampled with an array of passive detectors, such as traps, or by searching polygons or transects. Models incorporating distance-dependent detection are fitted by maximizing the likelihood. Tools are included for data manipulation and model selection.