View source: R/compute_frequency_analysis.R

compute_frequency_analysis | R Documentation |

Performs a volume frequency analysis on custom data. Defaults to ranking by minimums; use `use_max`

for to
rank by maximum flows. Calculates the statistics from events and flow values provided. Columns of events (e.g. years), their
values (minimums or maximums), and identifiers (low-flows, high-flows, etc.). Function will calculate using all values in the
provided data (no grouped analysis). Analysis methodology replicates that from
HEC-SSP. Returns a list of tibbles and plots.

```
compute_frequency_analysis(
data,
events = Year,
values = Value,
measures = Measure,
use_max = FALSE,
use_log = FALSE,
prob_plot_position = c("weibull", "median", "hazen"),
prob_scale_points = c(0.9999, 0.999, 0.99, 0.9, 0.5, 0.2, 0.1, 0.02, 0.01, 0.001,
1e-04),
compute_fitting = TRUE,
fit_distr = c("PIII", "weibull"),
fit_distr_method = ifelse(fit_distr == "PIII", "MOM", "MLE"),
fit_quantiles = c(0.975, 0.99, 0.98, 0.95, 0.9, 0.8, 0.5, 0.2, 0.1, 0.05, 0.01),
plot_curve = TRUE,
plot_axis_title = "Discharge (cms)"
)
```

`data` |
A data frame of data that contains columns of events, flow values, and measures (data type). |

`events` |
Column in |

`values` |
Column in |

`measures` |
Column in |

`use_max` |
Logical value to indicate using maximums rather than the minimums for analysis. Default |

`use_log` |
Logical value to indicate log-scale transforming of flow data before analysis. Default |

`prob_plot_position` |
Character string indicating the plotting positions used in the frequency plots, one of |

`prob_scale_points` |
Numeric vector of probabilities to be plotted along the X axis in the frequency plot. Inverse of
return period. Default |

`compute_fitting` |
Logical value to indicate whether to fit plotting positions to a distribution. If 'FALSE' the output will
return only the data, plotting positions, and plot. Default |

`fit_distr` |
Character string identifying the distribution to fit annual data, one of |

`fit_distr_method` |
Character string identifying the method used to fit the distribution, one of |

`fit_quantiles` |
Numeric vector of quantiles to be estimated from the fitted distribution.
Default |

`plot_curve` |
Logical value to indicate plotting the computed curve on the probability plot. Default |

`plot_axis_title` |
Character string of the plot y-axis title. Default |

A list with the following elements:

`Freq_Analysis_Data` |
Data frame with provided data for analysis. |

`Freq_Plot_Data` |
Data frame with plotting positions used in frequency plot. |

`Freq_Plot` |
ggplot2 object with plotting positions and (optional) fitted curve. |

`Freq_Fitting` |
List of fitted objects from fitdistrplus. |

`Freq_Fitted_Quantiles` |
Data frame with fitted quantiles. |

```
## Not run:
# Working example:
# Calculate some values to use for a frequency analysis
# (requires years, values for those years, and the name of the measure/metric)
low_flows <- calc_annual_lowflows(station_number = "08NM116",
start_year = 1980,
end_year = 2000,
roll_days = 7)
low_flows <- dplyr::select(low_flows, Year, Value = Min_7_Day)
low_flows <- dplyr::mutate(low_flows, Measure = "7-Day")
# Compute the frequency analysis using the default parameters
results <- compute_frequency_analysis(data = low_flows,
events = Year,
values = Value,
measure = Measure)
## End(Not run)
```

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