numDeriv, rcdd, geometry (>= 0.3-6), proxy, spaMM (>= 1.7.2),
lattice, Rcpp (>= 0.12.10), nloptr, MASS

Read and Write FWF Files in the Blaise Format
person("Sjoerd", "Ophof", email = "sjoerd.ophof@gmail.com",
role = c("aut", "cre"))
Can be used to read and write a fwf with an accompanying blaise datamodel.
When supplying a datamodel for writing, the dataframe will be automatically converted
to that format and checked for compatibility.
Supports dataframes, tibbles and LaF objects.
testthat, LaF (>= 0.6.3), knitr, rmarkdown
'clean_model.R' 'generics.R' 'utils.R' 'variable.R' 'model.R'
'convert_df.R' 'convert_type.R' 'get_model.R'
'read_custom_types.R' 'read_data.R' 'read_data_laf.R'
'read_fwf_blaise.R' 'read_model.R' 'variable_custom.R'
'variable_date.R' 'variable_dummy.R' 'variable_enum.R'
'variable_integer.R' 'variable_real.R' 'variable_string.R'
'write_data.R' 'write_datamodel.R' 'write_fwf_blaise.R'
'write_fwf_blaise_with_model.R'

Read and Write FWF Files in the 'Blaise' Format
Can be used to read and write a fwf with an accompanying 'Blaise' datamodel.
Blaise is the software suite built by Statistics Netherlands (CBS). It is essentially a
way to write and collect surveys and perform statistical analysis on the data. It stores its data in
fixed width format with an accompanying metadata file, this is the Blaise format. The package automatically
interprets this metadata and reads the file into an R dataframe.
When supplying a datamodel for writing, the dataframe will be automatically converted
to that format and checked for compatibility.
Supports dataframes, tibbles and LaF objects.
For more information about 'Blaise', see <https://blaise.com/products/general-information>.

Carries out Bland Altman analyses (also known as a Tukey
mean-difference plot) as described by JM Bland and DG Altman in
1986 <doi:10.1016/S0140-6736(86)90837-8>. This package was created in
2015 as existing Bland-Altman analysis functions did not calculate
confidence intervals. This package was created to rectify this,
and create reproducible plots.
person("Deepankar", "Datta", email = "deepankardatta@nhs.net",
role = c("aut", "cre"))
'blandr.basic.plot.r' 'blandr.data.preparation.r'
'blandr.ggplot.r' 'blandr.plot.limits.r' 'blandr.statistics.r'
'blandr.draw.r' 'blandr.display.r' 'blandr.display.and.draw.r'
'blandr.display.and.plot.r' 'blandr.method.comparison.r'
'blandr.plot.r' 'blandr.proportional.bias.r'