calibration_sampler {Xcertainty}R Documentation

MCMC sampler for calibration data

Description

Build an MCMC sampler that only uses calibration data to estimate measurement error parameters

Usage

calibration_sampler(data, priors, package_only = FALSE)

Arguments

data

Photogrammetric data formatted for Xcertainty models, required to be an object with class obs.parsed, which can be obtained by running parse_observations()

priors

list with components that define the model's prior distribution. See help("flatten_data") for more details.

package_only

TRUE to return the formatted data used to build the sampler, otherwise FALSE to return the sampler

Value

outputs a function to run a sampler, the function arguments are:

niter

set the number of iterations

burn

set the number samples to discard

thin

set the thinning rate

Examples

# load example wide-format data
data("calibration")

# parse calibration study
calibration_data = parse_observations(
  x = calibration, 
  subject_col = 'CO.ID',
  meas_col = 'Lpix', 
  tlen_col = 'CO.L', 
  image_col = 'image', 
  barometer_col = 'Baro_Alt',
  laser_col = 'Laser_Alt', 
  flen_col = 'Focal_Length', 
  iwidth_col = 'Iw', 
  swidth_col = 'Sw',
  uas_col = 'uas'
)

# build sampler
sampler_data = calibration_sampler(
  data = calibration_data,
  priors = list(
    image_altitude = c(min = 0.1, max = 130),
    altimeter_bias = rbind(
      data.frame(altimeter = 'Barometer', mean = 0, sd = 1e2),
      data.frame(altimeter = 'Laser', mean = 0, sd = 1e2)
    ),
    altimeter_variance = rbind(
      data.frame(altimeter = 'Barometer', shape = .01, rate = .01),
      data.frame(altimeter = 'Laser', shape = .01, rate = .01)
    ),
    altimeter_scaling = rbind(
      data.frame(altimeter = 'Barometer', mean = 1, sd = 1e1),
      data.frame(altimeter = 'Laser', mean = 1, sd = 1e1)
    ),
    pixel_variance = c(shape = .01, rate = .01)
  ),
  # set to false to return sampler function
  package_only = TRUE
)

[Package Xcertainty version 1.0.1 Index]