Smoothing for Stream Network Data

Fits flexible additive models to data on stream networks, taking account of flow-connectivity of the network. Models are fitted using penalised least squares.


CHANGES IN VERSION 2.1.1 30/03/2017

- updated network names in examples to avoid error due to attempt to overwrite a network 

CHANGES IN VERSION 2.1 29/08/2016

- network(max.df = ...) removed and replaced with network(fixed.df = ...), for fixing the 
  degrees of freedom in a network smooth.
- parameter combinations causing optimiser to encounter singular penalty matrices are now 
- fixed error with control = list(approx = 1) 
- cyclical smooths via m(X, cyclical = T) and interactions via m(X, Y, cyclical = c(T, F))
- n-dimensional smooth accepted using m()
- removed ``network-node'' option for plot.smnet
- removed dependency on 'igraphs'

CHANGES IN VERSION 2.0 08/06/2015

- get_adjacency and smnet reworked so that SSN objects with multiple networks supported.  
  get_adjacency now returns a list containing the adjacency matrix and the binary id table 
  from the SSN object.
- significant changes to plotting of spatial networks
- dependence on 'dfoptim' package not required, optimiser changed to 'optim()'
- show_weights() function added for exploring valid weights in data
- automatic Shreve weights, "autoShreve"", option added for 'weights' argument in network if 
  valid weights are not available
- examples updated 

Reference manual

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2.1.2 by Alastair Rushworth, a year ago

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Browse source code at

Authors: Alastair Rushworth

Documentation:   PDF Manual  

GPL-2 license

Imports graphics, grDevices, methods, RSQLite, spam, splines, stats

Depends on SSN

Suggests testthat

See at CRAN