Description Usage Arguments Value Examples
Calculates the maximum likelihood estimator for the parameter alpha of a Pareto distribution with a known threshold and (if applicable) a known truncation
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losses |
Numeric vector. Losses that are used for the ML estimation. |
t |
Numeric. Threshold of the Pareto distribution. |
truncation |
Numeric. If |
reporting_thresholds |
Numeric vector. Allows to enter loss specific reporting thresholds. If |
is.censored |
Logical vector. |
weights |
Numeric vector. Weights for the losses. For instance |
alpha_min |
Numeric. Lower bound for alpha (only used in truncated case). |
alpha_max |
Numeric. Upper bound for alpha (only used in truncated case). |
Maximum likelihood estimator for the parameter alpha
of a Pareto distribution with threshold t
given the observations losses
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | losses <- rPareto(100, 1000, 2)
Pareto_ML_Estimator_Alpha(losses, 1000)
losses <- rPareto(100, 1000, 2, truncation = 2000)
Pareto_ML_Estimator_Alpha(losses, 1000)
Pareto_ML_Estimator_Alpha(losses, 1000, truncation = 2000)
t <- 100
alpha <- 2
losses <- rPareto(10000, t, alpha)
reporting_thresholds <- rPareto(10000, t, 5)
index <- losses > reporting_thresholds
losses <- losses[index]
reporting_thresholds <- reporting_thresholds[index]
Pareto_ML_Estimator_Alpha(losses, t)
Pareto_ML_Estimator_Alpha(losses, t, reporting_thresholds = reporting_thresholds)
losses <- rPareto(10, 1000, 2)
w <- rep(1, 10)
w[1] <- 3
losses2 <- c(losses, losses[1], losses[1])
Pareto_ML_Estimator_Alpha(losses, 1000, weights = w)
Pareto_ML_Estimator_Alpha(losses2, 1000)
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