Description Usage Arguments Value Note Author(s) References Examples
It computes the combination of probability distributions according to few parameters.
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ncomb.prob(x, y = NULL, independent = !is_nothing(nsample),
lower.plausible = 0, upper.plausible = 1, method.name = character(0),
nsample = numeric(0), tolerance = 0.005, arithmetic = TRUE,
loss.type = c("information","quadratic","harmonic","geometric","logarithmic",
"evidential"), plots = FALSE,...)
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x |
List of numeric vectors of probabilities or a numeric vector of probabilities (see note). |
y |
A numeric vector of probabilities. Default is NULL (see note). |
tolerance |
Small quantity to control the failure of the method. |
independent |
Logical. If independent=TRUE, one weight is computed, otherwise one weight is computed per pair of elements to be combined (see note). |
lower.plausible |
A number within [0,1]. |
upper.plausible |
A number within [0,1]. |
method.name |
Names of the probabilities distributions to be combined. |
nsample |
Number of samples (for Monte Carlo). |
arithmetic |
Logical. If arithmetic=FALSE, the logarithmic approach is applied. |
loss.type |
specifies loss function type: "information", "quadratic", "harmonic", "geometric", "logarithmic", "evidential". |
plots |
option to plot (plot=TRUE) the input and output probabilities. |
... |
Other numeric vectors of probabilities to combine and further arguments passed to function optimize. |
A list:
combined |
A numeric vector that results of the combination of the data. |
weight |
Computed weights: a numeric value (if input independent=TRUE) or vector (if input independent=FALSE) with elements in [0,1]. |
info |
Other information. |
- All input vectors elements must be within [0,1]
- If input vectors do not have names, they will be created (see examples).
- Elements of different vectors with same names are those to be combined.
- If the input y = NULL and x is a numeric vector all its elements will be combined.
Code: David R. Bickel and Marta Padilla (modifications)
Documentation: Alaa Ali and Marta Padilla
Bickel, D. R. (2012). Game-theoretic probability combination with applications to resolving conflicts between statistical methods. International Journal of Approximate Reasoning, 53, 880-891.
1 2 3 4 5 6 7 8 9 10 | #Two probability distributions to combine
x1<-c(a = 0.5, b = 0.2, d = NA, e = 0, 0.3, 0.8)
x2<-c(b = 0.4, a = 0.3, e = NA, b = 0.2 , 0.13, 0.28)
z1 <- ncomb.prob(x = x1,y= x2,independent=TRUE)
z2 <- ncomb.prob(x = list(X1=x1,X2=x2),independent=FALSE)
#not yet implemented for independent=TRUE:
z3 <- ncomb.prob(x = x1,independent=FALSE,loss.type="quadratic")
z4 <- ncomb.prob(x = as.list(x1),independent=FALSE)
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