Kalman Filter for Impulse Noised Outliers
c(
person("Bertrand", "Cloez", email = "bertrand.cloez@inrae.fr", role = c("aut")),
person("Isabelle", "Sanchez", email = "isabelle.sanchez@inrae.fr", role = c("aut", "cre")),
person("Benedicte", "Fontez", email = "benedicte.fontez@supagro.fr", role = c("ctr")))
Bertrand Cloez [aut],
Isabelle Sanchez [aut, cre],
Benedicte Fontez [ctr]
A method for detecting outliers with a Kalman filter on impulsed
noised outliers and prediction on cleaned data. 'kfino' is a robust
sequential algorithm allowing to filter data with a large number of outliers.
This algorithm is based on simple latent linear Gaussian processes as in the
Kalman Filter method and is devoted to detect impulse-noised outliers. These
are data points that differ significantly from other observations. 'ML'
(Maximization Likelihood) and 'EM' (Expectation-Maximization algorithm)
algorithms were implemented in 'kfino'. The method is described in full
details in the following arXiv e-Print: <arXiv:2208.00961>.
rmarkdown, knitr, testthat (>= 3.0.0), covr, foreach,
doParallel, parallel

c(person("Chelsey", "Bryant", email = "clb117@case.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-3603-4854")),
person("Nicholas R.", "Wheeler", email = "nrw16@case.edu", role = c("aut"), comment = c(ORCID = "0000-0003-2248-8919")),
person("Franz", "Rubel", email = "franz.rubel@vetmeduni.ac.at", role = c("aut"), comment = c(ORCID = "0000-0002-0048-7379")),
person("Roger H.", "French", email = "rxf131@case.edu", role = c("aut"), comment = c(ORCID = "0000-0002-6162-0532")))
Aids in identifying the Koeppen-Geiger (KG) climatic zone for
a given location. The Koeppen-Geiger climate zones were first published in 1884, as a system
to classify regions of the earth by their relative heat and humidity through the year, for
the benefit of human health, plant and agriculture and other human activity [1]. This climate
zone classification system, applicable to all of the earths surface, has continued to be
developed by scientists up to the present day.  Recently one of use (FZ) has published updated,
higher accuracy KG climate zone definitions [2]. In this package we use these updated
high-resolution maps as the data source [3]. We provide functions that return the KG climate zone
for a given longitude and lattitude, or for a given United States zip code. In addition
the CZUncertainty() function will check climate zones nearby to check if the given location
is near a climate zone boundary. In addition an interactive shiny app is provided to define
the KG climate zone for a given longitude and lattitude, or United States zip code.
Digital data, as well as animated maps, showing the shift of the climate zones are provided
on the following website <http://koeppen-geiger.vu-wien.ac.at>.
This work was supported by the DOE-EERE SunShot award DE-EE-0007140.
[1] W. Koeppen, (2011) <doi:10.1127/0941-2948/2011/105>.
[2] F. Rubel and M. Kottek, (2010) <doi:10.1127/0941-2948/2010/0430>.
[3] F. Rubel, K. Brugger, K. Haslinger, and I. Auer, (2016) <doi:10.1127/metz/2016/0816>.