Re: spikes in contour and persp (PR#327)

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Subject: Re: spikes in contour and persp (PR#327)
ripley@stats.ox.ac.uk
Date: Tue 16 Nov 1999 - 21:03:08 EST


Message-Id: <199911161103.MAA15162@pubhealth.ku.dk>

> From: jlindsey@alpha.luc.ac.be
> Date: Tue, 16 Nov 1999 08:57:00 +0100 (MET)
>
> The following matrix of normed likelihoods should give a smooth
> surface but instead gives a series of spikes in both persp and contour
> (the dim labels are the axes values). I know an algorithm cannot be
> infallible but it would be nice to have some parameters to control the
> smoothing. (It takes close to an hour to produce this matrix on a
> Pentium II 300mh. It was after that that it crashed with the Inf in my
> previous bug message...)

I am sorry, but I don't understand. contour does not do any
smoothing, but interpolates assuming smoothness. The data
appears to me to be a series of spikes just off the diagonal, and not
what contour thinks of as a smooth surface. It is common to
interpolate the data from such a coarse grid before contouring.

persp just plots the data with visual linear interpolation.

> round(like*100,0)
     2.32 2.345 2.37 2.395 2.42 2.445 2.47 2.495 2.52 2.545 2.57 2.595 2.62
1.4 0 0 0 0 0 0 0 0 0 0 0 0 0
1.42 0 1 0 0 0 0 0 0 0 0 0 0 0
1.44 0 1 2 0 0 0 0 0 0 0 0 0 0
1.46 0 0 2 5 0 0 0 0 0 0 0 0 0
1.48 0 0 0 7 9 0 0 0 0 0 0 0 0
1.5 0 0 0 1 17 15 1 0 0 0 0 0 0
1.52 0 0 0 0 3 34 21 1 0 0 0 0 0
1.54 0 0 0 0 0 6 57 26 1 0 0 0 0
1.56 0 0 0 0 0 0 12 79 29 1 0 0 0
1.58 0 0 0 0 0 0 0 19 95 29 1 0 0
1.6 0 0 0 0 0 0 0 1 26 100 26 1 0
1.62 0 0 0 0 0 0 0 0 1 31 93 22 0
1.64 0 0 0 0 0 0 0 0 0 1 32 77 17
1.66 0 0 0 0 0 0 0 0 0 0 2 28 59
1.68 0 0 0 0 0 0 0 0 0 0 0 2 23
1.7 0 0 0 0 0 0 0 0 0 0 0 0 1
1.72 0 0 0 0 0 0 0 0 0 0 0 0 0
1.74 0 0 0 0 0 0 0 0 0 0 0 0 0
1.76 0 0 0 0 0 0 0 0 0 0 0 0 0
1.78 0 0 0 0 0 0 0 0 0 0 0 0 0
1.8 0 0 0 0 0 0 0 0 0 0 0 0 0
     2.645 2.67 2.695 2.72 2.745
1.4 0 0 0 0 0
1.42 0 0 0 0 0
1.44 0 0 0 0 0
1.46 0 0 0 0 0
1.48 0 0 0 0 0
1.5 0 0 0 0 0
1.52 0 0 0 0 0
1.54 0 0 0 0 0
1.56 0 0 0 0 0
1.58 0 0 0 0 0
1.6 0 0 0 0 0
1.62 0 0 0 0 0
1.64 0 0 0 0 0
1.66 13 0 0 0 0
1.68 41 0 0 0 0
1.7 16 0 6 0 0
1.72 1 0 16 4 0
1.74 0 0 6 10 3
1.76 0 0 1 4 5
1.78 0 0 0 0 2
1.8 0 0 0 0 0

If I do some interpolation

library(akima)
x <- as.numeric(rownames(like))
y <- as.numeric(colnames(like))
xx <- expand.grid(x=x, y=y)
like1 <- interp(xx$x, xx$y, like, seq(1.4, 1.8, len=50), seq(2.3, 2.8, len=50))
contour(like1$x, like1$y,like1$z)

I get a slightly smoother result, but still five peaks. (Are the
values for col=2.67 correct?)

I guess you need to evaluate this on a finer grid near the diagonal,
and probably adjust the coordinate system to get enough resolution
on the anti-diagonal.

-- 
Brian D. Ripley,                  ripley@stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272860 (secr)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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