inst/doc/SSM_fitting.R

In ianjonsen/foieGras: Fit Continuous-Time State-Space and Latent Variable Models for Quality Control of Argos Satellite (and Other) Telemetry Data and for Estimating Changes in Animal Movement

## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
require(dplyr)
require(patchwork)
require(aniMotum)

## ----pre-processing, message=FALSE--------------------------------------------
fit_ssm(ellie, 
        vmax = 3, 
        pf = TRUE)

## ----model fit, message=FALSE, eval=FALSE-------------------------------------
#  fit <- fit_ssm(ellie,
#                 model = "rw",
#                 time.step = 24)

## ----emf, message=FALSE-------------------------------------------------------
emf()

## ----emf mod, message=FALSE, fig.width=7, fig.height=6------------------------
emf2 <- mutate(emf(), emf.x = c(0.1, 1, 2, 4, 20, 8, 15, 15))

fit1 <- fit_ssm(subset(sese2, id == unique(id)[1]), 
                model = "rw", 
                time.step=24, 
                control = ssm_control(verbose = 0))

fit2 <- fit_ssm(subset(sese2, id == unique(id)[1]), 
                model = "rw", 
                time.step=24, 
                emf = emf2, 
                control = ssm_control(verbose = 0))

par(mfrow = c(2,1), mar = c(4,3,1,1))

hist(grab(fit1, "f")$x - grab(fit2, "f")$x, breaks = 20, 
     main = "fit1$x - fit2$x", xlim = c(-20,20), xlab = "")

hist(grab(fit1, "f")$y - grab(fit2, "f")$y, breaks = 20, 
     main = "fit1$y - fit2$y", xlim = c(-20,20), xlab = "Distance (km)")

## ----demonstrate map use, message=FALSE, warning=FALSE------------------------
fit1 <- fit_ssm(ellie, 
                model = "crw", 
                time.step = 24,
                control = ssm_control(verbose = 0))

fit2 <- fit_ssm(ellie, 
                model = "crw", 
                time.step = 24, 
                map = list(psi = factor(NA)),
                control = ssm_control(verbose = 0))

c(fit1$ssm[[1]]$AICc, fit2$ssm[[1]]$AICc)

## ----ssm_control, message=FALSE, warning=FALSE, eval = FALSE------------------
#  fit <- fit_ssm(ellie,
#                 model = "crw",
#                 time.step = 24,
#                 control = ssm_control(optim = "optim",
#                                       verbose = 0))

## ----optimizer params, message=FALSE, warning=FALSE, eval = FALSE-------------
#  fit <- fit_ssm(ellie,
#                 model = "crw",
#                 time.step = 24,
#                 control = ssm_control(optim = "optim",
#                                       maxit = 1000,
#                                       verbose = 0))