Showing 3 of total 3 results (show query)
gtromano
DeCAFS:Detecting Changes in Autocorrelated and Fluctuating Signals
Detect abrupt changes in time series with local fluctuations as a random walk process and autocorrelated noise as an AR(1) process. See Romano, G., Rigaill, G., Runge, V., Fearnhead, P. (2021) <doi:10.1080/01621459.2021.1909598>.
Maintained by Gaetano Romano. Last updated 2 years ago.
change-detectionchangepoint-detectiontime-series-analysiscpp
2 stars 3.00 score 2 scripts
jskoien
intamap:Procedures for Automated Interpolation
Geostatistical interpolation has traditionally been done by manually fitting a variogram and then interpolating. Here, we introduce classes and methods that can do this interpolation automatically. Pebesma et al (2010) gives an overview of the methods behind and possible usage <doi:10.1016/j.cageo.2010.03.019>.
Maintained by Jon Olav Skoien. Last updated 1 years ago.
1 stars 2.61 score 68 scripts 2 dependents
cran
psgp:Projected Spatial Gaussian Process Methods
Implements projected sparse Gaussian process Kriging (Ingram 'et. al.', 2008, <doi:10.1007/s00477-007-0163-9>) as an additional method for the 'intamap' package. More details on implementation (Barillec 'et. al.', 2010, <doi:10.1016/j.cageo.2010.05.008>).
Maintained by Ben Ingram. Last updated 1 years ago.
1.00 score