Lattice.
Inputting data one pixel at a time (nov8.s).
Image plot (nov8.s).					
Pocket plot (nov8.s).
Convert to geostatistical data (nov8.s).
Median polish (medpolish1.r).
Variogram (and variogram of median polish residuals) (nov8.s).

Geostat.
Fit spatial trend by regression and show residuals (nov17.s).
Smooth onto a lattice (nov17.s).
Variogram estimate (nov8.s).
Estimate spherical or rational quadratic variogram (nov15.s).
Simulate a Gaussian Random Field with a given variogram (nov17.s).
Fit a polynomial surface (nov15.s).
Kriging (nov15.s).

P.P.
Inputting data with a mouse (nov8.s).
Plot with a map (nov15.s).
Convert to lattice data of quadrat counts on a grid (nov15.s).
Store as geostatistical data (nov15.s)
 (... and then do geostatistical stuff like variogram and kriging.)
Kernel smoothing (nov17.s).
Smooth onto a lattice (nov17.s).
K-function and L-function (pp2.s).
Confidence bounds on the K-function and L-function (pp2.s).
F-function (nov17.s).
G-function (nov17.s).
J-function (nov17.s).
Simulate a Neyman-Scott process, Matern(I) process, or SSI process (pp2.s).
Fit a pseudo-likelihood model (nov22.s).
Plot background rate and fitted model for the rate (nov22.s).

Marked P.P.
Plot (nov22.s).
J-function, K-function, L-function (nov22.s).
kernel smoothing (nov22.s).
Convert to quadrat totals (nov22.s).
Fit a pseudo-likelihood model (nov22.s).
Plot background rate and fitted model for the rate (nov22.s).