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bam_check_args()
|
Performs the following checks:
- types:
- logQ_hat is numeric vector
- everything else matrix
- dimensions:
- all matrices have same dims
- logQ_hat has length equal to ncol of matrices |
|
bam_check_nas()
|
Add missing-data inputs to data list |
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bam_data()
|
Preprocess data for BAM estimation |
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bam_estimate()
|
Estimate BAM |
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bam_hydrograph()
|
Plot flow time series from BAM inference |
|
bam_plot(<bamdata>)
|
Plot a bamdata object |
|
bam_plot(<bamval>)
|
Plot a bamval object to show predictive performance |
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bam_plot()
|
Plot a geoBAMr-created object |
|
bam_priors()
|
Establish prior hyperparameters for BAM estimation |
|
bam_qpred()
|
Flow posterior mean and Bayesian credible interval. |
|
bam_settings()
|
Options manager for geoBAMr defaults |
|
bam_settings_unsupervised()
|
Options manager for geoBAMr defaults using unsupervised classification |
|
bam_valdata()
|
Create a data.frame for BAM validation |
|
bam_validate()
|
Calculate validation metrics and plots |
|
classify_func()
|
Classify river for expert framework |
|
classify_func_unsupervised()
|
Classify river for unsupervised framework |
|
CoV()
|
Coefficient of variation |
|
cv2sigma()
|
Convert coefficient of variation to sigma parameter of lognormal diistribution |
|
Ej()
|
E_j general efficiency statistic from Criss and Winston (2008) |
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estimate_A0SD()
|
Estimate base cross-sectional area SD using bam data |
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estimate_A0SD_unsupervised()
|
Estimate base cross-sectional area SD using bam data |
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estimate_b()
|
Estimate AHG b exponent using bam data |
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estimate_bSD()
|
Estimate AHG b SD using bam data |
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estimate_bSD_unsupervised()
|
Estimate AHG b SD using bam data |
|
estimate_b_unsupervised()
|
Estimate AHG b exponent using bam data |
|
estimate_logA0()
|
Estimate base cross-sectional area using bam data |
|
estimate_logA0_unsupervised()
|
Estimate base cross-sectional area using bam data |
|
estimate_logDb()
|
Estimate bankful depth using bam data |
|
estimate_logDbSD()
|
Estimate bankful depth SD using bam data |
|
estimate_logDbSD_unsupervised()
|
Estimate bankful depth SD using bam data |
|
estimate_logDb_unsupervised()
|
Estimate bankful depth using bam data |
|
estimate_logn()
|
Estimate manning's n using bam data |
|
estimate_lognSD()
|
Estimate manning's n SD using bam data |
|
estimate_lognSD_unsupervised()
|
Estimate manning's n SD using bam data |
|
estimate_logn_unsupervised()
|
Estimate manning's n using bam data |
|
estimate_logr()
|
Estimate channel shape using bam data |
|
estimate_logrSD()
|
Estimate channel shape SD using bam data |
|
estimate_logrSD_unsupervised()
|
Estimate channel shape SD using bam data |
|
estimate_logr_unsupervised()
|
Estimate channel shape using bam data |
|
estimate_logWb()
|
Estimate bankful width using bam data |
|
estimate_logWbSD()
|
Estimate bankful width SD using bam data |
|
estimate_logWbSD_unsupervised()
|
Estimate bankful width SD using bam data |
|
estimate_logWb_unsupervised()
|
Estimate bankful width using bam data |
|
estimate_lowerboundA0()
|
Estimate base cross-sectional area lowerbound using bam data |
|
estimate_lowerboundA0_unsupervised()
|
Estimate base cross-sectional area lowerbound using bam data |
|
estimate_lowerboundb()
|
Estimate AHG b lowerbound using bam data |
|
estimate_lowerboundb_unsupervised()
|
Estimate AHG b lowerbound using bam data |
|
estimate_lowerboundlogDb()
|
Estimate bankful depth lower bound using bam data |
|
estimate_lowerboundlogDb_unsupervised()
|
Estimate bankful depth lower bound using bam data |
|
estimate_lowerboundlogn()
|
Estimate manning's n lowerbound using bam data |
|
estimate_lowerboundlogn_unsupervised()
|
Estimate manning's n lowerbound using bam data |
|
estimate_lowerboundlogr()
|
Estimate channel shape lowerbound using bam data |
|
estimate_lowerboundlogr_unsupervised()
|
Estimate channel shape lowerbound using bam data |
|
estimate_lowerboundlogWb()
|
Estimate bankful width lower bound using bam data |
|
estimate_lowerboundlogWb_unsupervised()
|
Estimate bankful width lower bound using bam data |
|
estimate_upperboundA0()
|
Estimate base cross-sectional area upperbound using bam data |
|
estimate_upperboundA0_unsupervised()
|
Estimate base cross-sectional area upperbound using bam data |
|
estimate_upperboundb()
|
Estimate AHG b upperbound using bam data |
|
estimate_upperboundb_unsupervised()
|
Estimate AHG b upperbound using bam data |
|
estimate_upperboundlogDb()
|
Estimate bankful depth upper bound using bam data |
|
estimate_upperboundlogDb_unsupervised()
|
Estimate bankful depth upper bound using bam data |
|
estimate_upperboundlogn()
|
Estimate manning's n upperbound using bam data |
|
estimate_upperboundlogn_unsupervised()
|
Estimate manning's n upperbound using bam data |
|
estimate_upperboundlogr()
|
Estimate channel shape upperbound using bam data |
|
estimate_upperboundlogr_unsupervised()
|
Estimate channel shape upperbound using bam data |
|
estimate_upperboundlogWb()
|
Estimate bankful width upper bound using bam data |
|
estimate_upperboundlogWb_unsupervised()
|
Estimate bankful width upper bound using bam data |
|
geoBAMr-package
|
The 'geoBAMr' package. |
|
ln_moms()
|
Calculate lognormal moments based on truncated normal parameters |
|
ln_sigsq()
|
Calculate lognormal sigma parameter based on truncated normal parameters |
|
logNSE()
|
NSE, computed on log-transformed residuals |
|
maxmin()
|
Maximum across xs of min across time of width |
|
minmax()
|
Minimum across xs of max across time of width |
|
MRR()
|
Mean relativ residual |
|
NRMSE()
|
Normalized root-mean-square error |
|
NSE()
|
Nash-Sutcliffe efficiency |
|
rBIAS()
|
Relative bias |
|
RRMSE()
|
Relative root-mean-square error |
|
sample_xs()
|
Take a random sample of a bamdata object's cross-sections. |
|
SDRR()
|
Standard deviation of relative residual |