Crop example demonstrating multiple years and user defined uStar-Seasons | Defining Seasons with different surface friction conditions | Uncertainty introduced by the uStar Threshold estimate: bootstrap | Using change point detection instead of moving point method for UStar Threshold estimation

Different treatments of uStar threshold | Not applying uStar filtering | User-specified uStar threshold | Single uStar threshold estimate | Scenarios across distribution of u* threshold estimate | See also

Overview | Usage | Difference between solar time and local time | Computing sun position | Sunrise and sunset | Further Utilities

Importing the half-hourly data | Estimating the uStar threshold distribution | Gap-filling | Partitioning net flux into GPP and Reco | Estimating the uncertainty of aggregated results | Storing the results in a csv-file

Aggregating uncertainty to daily and annual values | Example setup | Omitting problematic records | Random error | Wrong aggregation without correlations | Considering correlations | Daily aggregation | u* threshold uncertainty | Combined aggregated uncertainty

bigleaf package replacing GeoFunctions of REddyProc | Vapour pressure deficit (VPD) | Evapotranspiration from latent heat and air temperature | Converting visible radiation from irradiance to photons flux | Potential and Extraterrestrial solar radiation

Basic usage | Distribution | Mean and Variance | Mode | Parameter Estimation

Approximating the difference of lognormal random variables | Two uncorrelated random variables | Test if difference is significantly different from zero | Two positively correlated variables | Subtracting a variable with larger variance

Two uncorrelated random variables | Many correlated variables | Generating observations and log-normally distributed random errors | Estimating the correlation matrix and effective number of parameters | Computing the mean and its standard deviation

Distribution | Shape by multiplicative standard deviation | Density, distribution function, quantile function and random generation | Expected value, Variance, Mode, and Median | Parameter Estimation from moments

Extended usage of the gap filling algorithm | Explicit demonstration of MDS algorithm for NEE gap filling