summary.starma: Summary method for space-time series fitted models

In starma: Modelling Space Time AutoRegressive Moving Average (STARMA) Processes

Description

summary method for class "starma".

Usage

## S3 method for class 'starma'
summary(object, ...)
## S3 method for class 'summary.starma'
print(x, ...)

Arguments

object	a starma class object.
x	a summary.starma class object.
...	unused

Details

print.summary.starma formats the coefficients, standard errors, etc. and additionally gives 'significance stars'.

Value

An object of class summary.starma containing the following elements:

call	An object of mode "call": a symbolic description of the fitted model
coefficients	A data frame containing the estimates, standard errors, etc. of the coefficients of the fitted model

Author(s)

Felix Cheysson

Examples

data(nb_mat)	# Get neighbourhood matrices

# Simulate a STARMA model
eps <- matrix(rnorm(94*200), 200, 94)
sim <- eps
for (t in 3:200) {
	sim[t,] <- (.4*diag(94) + .25*blist[[2]]) %*% sim[t-1,] +
		(.25*diag(94)                ) %*% sim[t-2,] +
		(            - .3*blist[[2]]) %*% eps[t-1,] +
		eps[t, ]
}

sim <- sim[101:200,]
sim <- stcenter(sim)	# Center and scale the dataset

# Select parameters to estimate
ar <- matrix(0, 2, 2)
ar[ ,1] <- 1	# phi10 and phi20
ar[1,2] <- 1	# phi11
ma <- matrix(c(0,1), 1, 2)	# theta11

# Run the Kalman filter algorithm
model <- starma(sim, blist, ar, ma)

# Get summary
summary(model)

Example output

Call:
starma.default(data = sim, wlist = blist, ar = ar, ma = ma)

         Estimate Std..Error t.value   p.value    
phi10    0.413569   0.010106 40.9216 < 2.2e-16 ***
phi11    0.229612   0.027557  8.3323 < 2.2e-16 ***
phi20    0.236001   0.010081 23.4095 < 2.2e-16 ***
theta11 -0.289258   0.034959 -8.2741 < 2.2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

starma documentation built on May 2, 2019, 1:26 p.m.