Influenza-Attributable Mortality with Distributed-Lag Models
c(person(given="Theodore", family="Lytras",
email="thlytras@gmail.com", role=c("aut","cre"),
comment=c(ORCID="0000-0002-4146-4122")),
person(given="Antonio", family="Gasparrini",
email="antonio.gasparrini@lshtm.ac.uk", role="ctb",
comment=c(ORCID="0000-0002-2271-3568")),
person(given="Shuangcai", family="Wang",
email="swang1@gmail.com", role="ctb"))
Functions to estimate the mortality attributable to
influenza and temperature, using distributed-lag nonlinear models
(DLNMs), as first implemented in
Lytras et al. (2019) <doi:10.2807/1560-7917.ES.2019.24.14.1800118>.
Full descriptions of underlying DLNM methodology in Gasparrini et al.
<doi:10.1002/sim.3940> (DLNMs),
<doi:10.1186/1471-2288-14-55> (attributable risk from DLNMs) and
<doi:10.1002/sim.5471> (multivariate meta-analysis).
Theodore Lytras [aut, cre] (<https://orcid.org/0000-0002-4146-4122>),
Antonio Gasparrini [ctb] (<https://orcid.org/0000-0002-2271-3568>),
Shuangcai Wang [ctb]

Estimation of background-subtracted fluorescence data
Simulate and analyse fluorescence data sets obtained from
calcium imaging experiments in living cells (such as neurons).
The package provide tools to estimate background-subtracted
fluorescence transients and build meaningful confidence
intervals on these estimations. This covers both the case of
homogeneous background fluorescence and that of Regions Of
Interest (ROI) displaying background inhomogeneities.
Background-subtracted fluorescence transients can be fitted
with monoexponential models or estimated pointwise.

Contains data sets from Bernard Flury (1997) A First Course in Multivariate Statistics, Springer NY
To be used in association with Flury's book

Contains data sets from Bernard Flury (1997) A First
Course in Multivariate Statistics, Springer NY

c(person(family = "Masinde", given = "Brian", role = c("aut", "cre"),
email= "masindeb@live.com"), person(family = "Bartoszek", given = "Krzysztof",
role = c("ctb", "ths"), email= "krzbar@protonmail.ch"))
Functions for range estimation in birds based on Pennycuick (2008)
and Pennycuick (1975), 'Flight' program which compliments Pennycuick (2008)
requires manual entry of birds which can be tedious when there are hundreds
of birds to estimate. Implemented are two ODE methods discussed in Pennycuick (1975)
and time-marching computation methods as in Pennycuick (1998) and Pennycuick (2008).
See Pennycuick (1975, ISBN:978-0-12-249405-5), Pennycuick (1998) <doi:10.1006/jtbi.1997.0572>,
and Pennycuick (2008, ISBN:9780080557816).
utils, Rcpp (>= 1.0.2), knitr, kableExtra, rmarkdown
'FlyingR.R' 'RcppExports.R' 'birds_documentation.R'
'constant_muscle_mass.R' 'constant_specific_power.R'
'constant_specific_work.R' 'control.R' 'method_2.R'
'method_1.R' 'input_match.R' 'lookup_table2.R'
'misc_functions.R' 'flight_simulation.R' 'migrate.R'
'stopover_mass_calculator.R' 'zzz.R'
Brian Masinde [aut, cre],
Krzysztof Bartoszek [ctb, ths]