add_knots.bmop | Add a new knot to a bmop object |
AIC.bmop | Akaike Information Criteria for bmop |
as.bins | Bins grouping |
as.function.bmop | Convert an bmop object to a function |
BIC.bmop | Bayesian Information Criteria for bmop |
bmop_fit | Estimation of bmop density or conditional density |
bmop_fit.bins | Estimation of bmop density or conditional density |
bmop_fit.data.frame | Estimation of bmop density or conditional density |
bmop_fit.default | Estimation of bmop density or conditional density |
bmop_fit.histogram | Estimation of bmop density or conditional density |
bmopPar | Set Rbmop parameters |
clean.bmop | Clean a bmop object |
comparison_plot | Plot several bmops and true density |
dim.bmop | Dimension of bmop |
envelope_plot | Envelop of estimated bmop |
evaluate.bmop | Evaluation of a bmop object |
Examples_bmop | Examples of bmop density estimations |
generate_knots | Generate sequence of knots for bmop objects |
integrate.bmop | Integrate bmop object over the support |
is.bmop | Check if an object's class is bmop |
KL.bmop | Kullback-Leibler (KL) divergence between bmop and true... |
logLik.bmop | Log-Likelihood of bmop object |
lower.bmop | Lower Limit of bmop |
marginalize.bmop | Marginalize a bmop |
mean.bmop | Mean value for a bmop density |
new_bmop | New bmop object |
normalize.bmop | Normalize a bmop |
plot.bmop | Plot of bmop object |
points.bmop | Plot points from bmop |
print.bmop | Print bmop objects |
put_evidence.bmop | Put evidence on a conditional bmop |
Rbmop | Rbmop: A package for handling and estimating densities and... |
search_bmop | Greedy penalized log-likelihood search |
squareError.bmop | Square Error between bmop and true density |
summary.bmop | Summary of a bmop object |
upper.bmop | Upper Limit of bmop |
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