An implementation of the National Information Platforms for 
    Nutrition or NiPN's analytic methods for assessing quality of anthropometric 
    datasets that include measurements of weight, height or length, middle upper 
    arm circumference, sex and age. The focus is on anthropometric status but 
    many of the presented methods could be applied to other variables.

Digital map data of Japan for choropleth mapping, including a circle cartogram.

Fast and Accurate Trisomy Prediction in Non-Invasive Prenatal
    Testing.

Provides transfusion-related differential tests on Near-infrared spectroscopy (NIRS) time series with detection limit, which contains two testing statistics: Mean Area Under the Curve (MAUC) and slope statistic. This package applied a penalized spline method within imputation setting. Testing is conducted by a nested permutation approach within imputation. Refer to Guo et al (2018) <doi:10.1177/0962280218786302> for further details.

Datasets for testing nonlinear regression routines.

Fundamental physical constants (Quantity, Value, Uncertainty, Unit) for 
    SI (International System of Units) and non-SI units, plus unit conversions
    Based on the data from NIST (National Institute of Standards and Technology, USA)

Contains data, code, and figures from Hill et al. 2018a (Journal of Experimental Marine Biology and Ecology; <DOI: 10.1016/j.jembe.2018.07.006>) and Hill et al. 2018b (Data In Brief <DOI: 10.1016/j.dib.2018.09.133>). Datasets document plant allometry, stem heights, nutrient and stable isotope content, and sediment denitrification enzyme assays. The data and analysis offer an examination of nitrogen uptake and allocation in two salt marsh plant species.

Noninferiority tests for difference in failure rates at a prespecified control rate or prespecified time. For details, see Fay and Follmann, 2016 <DOI:10.1177/1740774516654861>.

Snow water equivalent is modeled with the process based 'delta.snow' model and empirical regression models using relationships between density and diverse at-site parameters. The methods are described in Winkler et al. (2021) <doi:10.5194/hess-25-1165-2021>, Guyennon et al. (2019) <doi:10.1016/j.coldregions.2019.102859>, Pistocchi (2016) <doi:10.1016/j.ejrh.2016.03.004>, Jonas et al. (2009) <doi:10.1016/j.jhydrol.2009.09.021> and Sturm et al. (2010) <doi:10.1175/2010JHM1202.1>.