Description Usage Arguments Details Value

Extract regression coefficients, variances, etc. from
fitted `dlMod`

objects

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | ```
coef(object, ...)
confint(object, ...)
Sigma(object, ...)
vcoef(object, ...)
vcoef0(object, ...)
## S4 method for signature 'dlMod'
Sigma(object, scaled = TRUE, ...)
## S4 method for signature 'dlMod'
vcoef0(object, scaled = TRUE, ...)
## S4 method for signature 'dlMod'
vcoef(object, scaled = TRUE, ...)
## S3 method for class 'dlMod'
coef(object, scaled = TRUE, ...)
## S3 method for class 'dlMod'
confint(object, parm, level = 0.95, scaled = TRUE,
coef = TRUE, ...)
``` |

`object` |
a fitted |

`...` |
additional arguments |

`scaled` |
if |

`parm` |
an integer or character index to subset parameters |

`level` |
the desired confidence level |

`coef` |
if |

Other typical methods like
`residuals`

, and `sigma`

, etc. are handled via inheritance
from lme4 classes.
If the argument `scaled = TRUE`

, parameter estimates are scaled
by the areas between radii and summed so that they can be interpreted
as the estimate up to a given radius (e.g. see the dlmBE
package documentation).

`coef.dlMod`

follows the format of

`lme4::coef.merMod`

to return the sums of fixed and random effects for each level and grouping factor`confint.dlMod`

returns confidence intervals for regression coefficients following

`stats::confint`

`Sigma`

returns the regression coefficient covariance matrix. Row and column indices are in the same order as

`vcoef`

(see below)`vcoef`

returns vectorized coefficients from the fitted model. Fixed effects come before distributed lag coefficients, which come before other random effects coefficients. For example, if

*β*is a vector of fixed effects;*θ_1*and*θ_2*are vectors of (separately penalized) DL coefficients; and*b_1*,*b_2*,*...*are additional random effects vectors for groups*1, 2, ...*, then`vcoef`

will return the (named) vector*(β', θ_1', θ_2', b_1', b_2', ...)'*.`vcoef0`

returns the same coefficient vector but without names (and is slightly faster).

All of these functions return `numeric`

data

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