lpnorm

Compute the Lp-norm of two sequencies.

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This work is an extension of the state space model for Poisson count data, Poisson-Gamma model, towards a semiparametric specification. Just like the generalized additive models (GAM), cubic splines are used for covariate smoothing. The semiparametric models are fitted by an iterative process that combines maximization of likelihood and backfitting algorithm.

Washington Junger

pgam

Poisson-Gamma Additive Models

lpnorm function

<dl> <dt>seq1</dt>
<dd>first sequency</dd> <dt>seq2</dt>
<dd>second sequency</dd> <dt>p</dt>
<dd>L-space of the norm. <code>0</code> is infinity norm or max norm, <code>1</code> is the absolute value norm, <code>2</code> is L2 norm and so on</dd></dl>

Arguments

Washington Leite Junger <a href="/link/wjunger%40ims.uerj.br?package=pgam&version=0.4.17" data-mini-rdoc="pgam::wjunger@ims.uerj.br">wjunger@ims.uerj.br</a>

Author

Utility function — lpnorm

<dl>

 <dt>seq1</dt>
<dd>first sequency</dd>

 <dt>seq2</dt>
<dd>second sequency</dd>

 <dt>p</dt>
<dd>L-space of the norm. <code>0</code> is infinity norm or max norm, <code>1</code> is the absolute value norm, <code>2</code> is L2 norm and so on</dd>

</dl>

Washington Leite Junger <a href='mailto:wjunger@ims.uerj.br'>wjunger@ims.uerj.br</a>

lpnorm: Utility function

Description

Usage

Value

Arguments

Author

See Also