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fitmix. Knowledge of most of
this is not useful. Use link{summary.ds.mixture}
for result summaries.
ds.mixture object has the following
elements: | distance |
| Vector of distances used in the analysis. |
| likelihood |
| Value of the log-likelihood at the maxima. |
| pars |
Parmeter
estimates. See mmds.pars for more
information. |
| mix.terms |
| Number of mixture terms fit. |
| width |
| Truncation distance used. |
| z |
List containing the matrix of covariates used. Output
from model.matrix. |
| zdim |
Number of
columns of z. See mmds.pars for more
information. |
| hessian |
| Hessian matrix at the maxima. |
| pt |
| Logical indicating whether the data were from a point transect survey. |
| data |
| Data frame after truncation. |
| ftype |
| Type of detection function. |
| ctrl.options |
Options passed to
optim. |
| showit |
| Debug level. |
| opt.method |
| Optimisation method used. |
| usegrad |
| Were analytic gradients used? |
| model.formula |
| Model formula. |
| mu |
| Per-observation effective trip width/effective area of detection. |
| pa.vec |
| Vector of per-observation detectabilities. |
| N |
| Estimate of N in the covered area (Horvitz-Thompson). |
| pa |
| Average detectability. |
| pars.se |
| Standard errors of the parameters. |
| N.se |
| Standard error of the Horvitz-Thompson estimate of the abundance. |
| pa.se |
| Standard error of the average detectability. |
| aic |
| AIC of the fitted model. |
| cvm |
Cramer-von Mises GoF
test results. List containing: p, the p-value and
W, the test statistic. |
| ks |
Kolmogorov-Smirnov test results. List containing:
p, the p-value and Dn, the test statistic.
See mmds.gof for more information. |
ds.mixture objects can be passed to
step.ds.mixture to select number of mixture
components based on AIC score.