Poisson Lognormal and Bivariate Poisson Lognormal Distribution

Analyzing Pointer Years and Components of Resilience
Marieke van der Maaten-Theunissen and Ernst van der Maaten
Marieke van der Maaten-Theunissen <marieketheunissen@gmail.com>
Functions to calculate and plot event and pointer years as well as components of resilience. Designed for dendroecological applications, but also suitable to analyze patterns in other ecological time series.

Functions to calculate and plot event and pointer years as well as
components of resilience. Designed for dendroecological applications, but also
suitable to analyze patterns in other ecological time series.

Marieke van der Maaten-Theunissen [aut, cph, cre, trl], Ernst van der Maaten [aut, trl], Gottfried Jetsckhe [aut, trl], Mario Trouillier [aut, trl]
Marieke van der Maaten-Theunissen <marieke.theunissen@tu-dresden.de>
Functions to calculate and plot event and pointer years as well as resilience indices. Designed for dendroecological applications, but also suitable to analyze patterns in other ecological time series.

Validation of Local and Remote Data Tables
Validate data in local data frames,
local 'tibble' objects, in 'CSV' and 'TSV' files,
and in database tables ('PostgreSQL' and 'MySQL').
Validation pipelines can be made using
easily-readable, consecutive validation steps
and such pipelines allow for switching of the
data table context. Upon execution of the
validation plan, several reporting options are
available. User-defined thresholds for failure
rates allow for the determination of appropriate
reporting actions (e.g., sending email
notifications).

Data Validation and Organization of Metadata for Local and
Remote Tables
Validate data in data frames, 'tibble' objects, 'Spark'
'DataFrames', and database tables. Validation pipelines can be made using
easily-readable, consecutive validation steps. Upon execution of the
validation plan, several reporting options are available. User-defined
thresholds for failure rates allow for the determination of appropriate
reporting actions. Many other workflows are available including an
information management workflow, where the aim is to record, collect, and
generate useful information on data tables.
c(
person("Richard", "Iannone", , "riannone@me.com", c("aut", "cre"),
comment = c(ORCID = "0000-0003-3925-190X")),
person("Mauricio", "Vargas", , "mvargas@dcc.uchile.cl", c("aut"),
comment = c(ORCID = "0000-0003-1017-7574"))
)
arrow, covr, crayon, data.table, duckdb, ggforce, ggplot2,
jsonlite, log4r, lubridate, RSQLite, RMySQL, RPostgres, readr,
rmarkdown, sparklyr, dittodb, odbc
Richard Iannone [aut, cre] (<https://orcid.org/0000-0003-3925-190X>),
Mauricio Vargas [aut] (<https://orcid.org/0000-0003-1017-7574>)