Description Details Author(s) References See Also Examples

Likelihood based population viability analysis in the presence of observation error and missing data. The package can be used to fit, compare, predict, and forecast various growth model types using data cloning.

The package implements data cloning based population viability analysis methodology developed by Nadeem and Lele (2012). This includes model estimation, model selection and forecasting of future population abundances for estimate the extinction risk of a population of interest.

`pva`

: main function for model fitting.

`model.select`

: main function for model model selection.

Growth models: `gompertz`

, `ricker`

,
`bevertonholt`

,
`thetalogistic`

, `thetalogistic_D`

.

Khurram Nadeem, Peter Solymos

Maintainer: Peter Solymos <solymos@ualberta.ca>

Nadeem, K., Lele S. R., 2012. Likelihood based population viability analysis in the presence of observation error. Oikos 121, 1656–1664.

1 2 3 4 5 6 7 8 9 10 11 | ```
## Not run:
## model selection for data with missing observations
data(songsparrow)
## model without observation error
m1 <- pva(songsparrow, gompertz("none"), 2, n.iter=1000)
## model with Poisson observation error
m2 <- pva(songsparrow, gompertz("poisson"), 2, n.iter=1000)
## model with Poisson observation error is strongly supported
model.select(m1, m2)
## End(Not run)
``` |

```
Loading required package: dcmle
Loading required package: dclone
Loading required package: coda
Loading required package: parallel
Loading required package: Matrix
dclone 2.1-2 2016-03-11
dcmle 0.3-1 2016-03-11
Attaching package: 'dcmle'
The following objects are masked from 'package:coda':
chanames, crosscorr.plot, gelman.diag, gelman.plot, geweke.diag,
heidel.diag, raftery.diag, varnames
Loading required package: stats4
PVAClone 0.1-6 2016-03-11
check out ?PVA for an overview
Compiling model graph
Resolving undeclared variables
Allocating nodes
Graph information:
Observed stochastic nodes: 48
Unobserved stochastic nodes: 3
Total graph size: 268
Initializing model
Compiling model graph
Resolving undeclared variables
Allocating nodes
Graph information:
Observed stochastic nodes: 48
Unobserved stochastic nodes: 51
Total graph size: 654
Initializing model
Compiling model graph
Resolving undeclared variables
Allocating nodes
Graph information:
Observed stochastic nodes: 24
Unobserved stochastic nodes: 24
Total graph size: 341
Initializing model
PVA Model Selection:
Time series with 24 observations (missing: 0)
Null Model: m1
Gompertz growth model without observation error
Alternative Model: m2
Gompertz growth model with Poisson observation error
log_LR delta_AIC delta_BIC delta_AICc
1 -90.73085 181.4617 181.4617 181.4617
Alternative Model is strongly supported over the Null Model
```

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