Summary methods for marssMLE objects — summary.marssMLE • MARSS

A brief summary of the fit: number of state and observation time series and the estimates. See also glance() and tidy() for other summary like output.

Usage

# S3 method for marssMLE
summary(object, digits = max(3, getOption("digits") - 3), ...)

Arguments

object: A marssMLE object.
digits: Number of digits for printing.
...: Not used.

Value

Returns `object` invisibly.

Author

Eli Holmes, NOAA, Seattle, USA.

Examples

  dat <- t(harborSeal)
  dat <- dat[c(2,11),]
  fit <- MARSS(dat)
#> Success! abstol and log-log tests passed at 26 iterations.
#> Alert: conv.test.slope.tol is 0.5.
#> Test with smaller values (<0.1) to ensure convergence.
#> 
#> MARSS fit is
#> Estimation method: kem 
#> Convergence test: conv.test.slope.tol = 0.5, abstol = 0.001
#> Estimation converged in 26 iterations. 
#> Log-likelihood: 11.74016 
#> AIC: -9.480311   AICc: -6.3692   
#>  
#>                                           Estimate
#> R.diag                                      0.0115
#> U.X.CoastalEstuaries                        0.0613
#> U.X.OR.NorthCoast                           0.0510
#> Q.(X.CoastalEstuaries,X.CoastalEstuaries)   0.0147
#> Q.(X.OR.NorthCoast,X.OR.NorthCoast)         0.0122
#> x0.X.CoastalEstuaries                       7.3823
#> x0.X.OR.NorthCoast                          6.2707
#> Initial states (x0) defined at t=0
#> 
#> Standard errors have not been calculated. 
#> Use MARSSparamCIs to compute CIs and bias estimates.
#> 
  
  summary(fit)
#> 
#> m: 2 state process(es) named X.CoastalEstuaries X.OR.NorthCoast
#> n: 2 observation time series named CoastalEstuaries OR.NorthCoast
#> 
#>                                        term   estimate
#> 1                                    R.diag 0.01148472
#> 2                      U.X.CoastalEstuaries 0.06134704
#> 3                         U.X.OR.NorthCoast 0.05099574
#> 4 Q.(X.CoastalEstuaries,X.CoastalEstuaries) 0.01468309
#> 5       Q.(X.OR.NorthCoast,X.OR.NorthCoast) 0.01218082
#> 6                     x0.X.CoastalEstuaries 7.38226633
#> 7                        x0.X.OR.NorthCoast 6.27067221
  glance(fit)
#>    coef.det      sigma df   logLik       AIC    AICc convergence errors
#> 1 0.9409488 0.03386941  7 11.74016 -9.480311 -6.3692           0      0
  tidy(fit)
#>                                        term   estimate   std.error     conf.low
#> 1                                    R.diag 0.01148472 0.005276236  0.001143482
#> 2                      U.X.CoastalEstuaries 0.06134704 0.025349650  0.011662644
#> 3                         U.X.OR.NorthCoast 0.05099574 0.022268900  0.007349500
#> 4 Q.(X.CoastalEstuaries,X.CoastalEstuaries) 0.01468309 0.008607225 -0.002186756
#> 5       Q.(X.OR.NorthCoast,X.OR.NorthCoast) 0.01218082 0.007267732 -0.002063677
#> 6                     x0.X.CoastalEstuaries 7.38226633 0.154075807  7.080283302
#> 7                        x0.X.OR.NorthCoast 6.27067221 0.231428782  5.817080133
#>      conf.up
#> 1 0.02182595
#> 2 0.11103145
#> 3 0.09464198
#> 4 0.03155295
#> 5 0.02642531
#> 6 7.68424937
#> 7 6.72426429