What to print. Default is "fit". If you input what as a vector, print returns a list. See examples.
"model" The model parameters with names for the estimated parameters. The output is customized by the form of the model that was fit. This info is in attr(x$model, "form") .
"par" A list of only the estimated values in each matrix. Each model matrix has it's own list element. Standard function: coef(x)
"start" or "inits" The values that the optimization algorithm was started at. Note, x$start shows this in form="marss" while print shows it in whatever form is in attr(x$model, "form") .
"paramvector" A vector of all the estimated values in each matrix. Standard function: coef(x, type="vector"). See coef.
"par.se","par.bias","par.lowCIs","par.upCIs" A vector the estimated parameter standard errors, parameter bias, lower and upper confidence intervals. Standard function: MARSSparamCIs(x) See MARSSparamCIs.
"xtT" or "states" The estimated states conditioned on all the data. x$states
"data" The data. This is in x$model$data
"logLik" The log-likelihood. Standard function: x$logLik. See MARSSkf for a discussion of the computation of the log-likelihood for MARSS models.
"ytT" The expected value of the data conditioned on all the data. Returns the data if present and the expected value if missing. This is in x$ytT (ytT is analogous to xtT).
"states.se" The state standard errors. x$states.se
"states.cis" Approximate confidence intervals for the states. See MARSSparamCIs.
"model.residuals" The one-step ahead model residuals or innovations. \(\mathbf{y}_t - E[\mathbf{y}_t|\mathbf{y}_1^{t-1}]\), aka actual data at time \(t\) minus the expected value of the data conditioned on the data from \(t=1\) to \(t-1\). Standard function: residuals(x, type="tt1") See MARSSresiduals for a discussion of residuals in the context of MARSS models.
"state.residuals" The smoothed state residuals. \(\mathbf{x}_t^T-E[\mathbf{x}_t|\mathbf{x}_{t-1}^T]\), aka the expected value of the states at time \(t\) conditioned on all the data minus the expected value of the states at time \(t\) conditioned on \(\mathbf{x}_{t-1}^T]\). Standard function: residuals(x, type="tT") See MARSSresiduals.
parameter name Returns the parameter matrix for that parameter with fixed values at their fixed values and the estimated values at their estimated values. Standard function: coef(x, type="matrix")$elem
"kfs" The Kalman filter and smoother output. See MARSSkf for a description of the output. The full kf output is not normally attached to the output from a MARSS() call. This will run the filter/smoother if needed and return the list invisibly. So assign the output as foo=print(x,what="kfs")
"Ey" The expectations involving y conditioned on all the data. See MARSShatyt for a discussion of these expectations. This output is not normally attached to the output from a MARSS() call--except ytT which is the predicted value of any missing y. The list is returned invisibly so assign the output as foo=print(x,what="Ey").