predict.dsm

a fitted <code><a href="/link/dsm?package=dsm&version=2.1.3" rd-options="" data-mini-rdoc="dsm::dsm">dsm</a></code> object as
  produced by <code>dsm()</code>.

object

spatially referenced covariates e.g.  sea
  temperature, depth, distance to shore, etc.  Note
  covariates in this dataframe must have names *identical*
  to variable names used in fitting the GAM.

newdata

area of each of the cells in the
  prediction grid. Ignored if if their is already a column
  in <code>newdata</code> called <code>off.set</code>.  The link
  function is applied to the offset inside this function.

off.set

what scale should the results be on. The
  default is <code>"response"</code> and is almost always what
  you want.

type

any other arguments passed to
  <code><a href="/link/predict.gam?package=dsm&version=2.1.3" rd-options="" data-mini-rdoc="dsm::predict.gam">predict.gam</a></code> or <code><a href="/link/predict.glm?package=dsm&version=2.1.3" rd-options="" data-mini-rdoc="dsm::predict.glm">predict.glm</a></code>.

Make predictions outside (or inside) the covered area.

This library implements density surface modelling of line
    transect data, based on the methods of Hedley et al. (2004). Some
    recent developments in the literature have also be incorporated.
    Outputs are point and interval estimates of population abundance
    and density.
    Please note that this version of dsm WILL NOT work with the Windows
    package DISTANCE. For a version that works with DISTANCE, please go
    to https://github.com/lenthomas/dsm-distance-6.1.
    For the latest version of dsm, please use the github version at the URL
    listed below.
    Miller, D. L., M. L. Burt, E. Rexstad and L. Thomas. 2013. Spatial
    models for distance sampling data: recent developments and future
    directions. Methods in Ecology and Evolution
    Hedley, S.L.,  S.T. Buckland and D.L. Borchers. 2004. "Spatial
    distance sampling methods" pp 48-70 in Advanced Distance Sampling,
    Buckland, S.T. et al. (eds). Oxford University Press.

predict.dsm: Predict from a fitted density surface model

Description

Usage

Arguments

Value