new Exponential(lambdaopt)
The constructor for a Exponential distribution object
Parameters:
| Name | Type | Attributes | Description |
|---|---|---|---|
lambda |
float |
<optional> |
Rate (inverse scale) parameter |
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Extends
Methods
(static) computeLambdaMinMSE(data)
Compute the Mean Square Error-minimising estimator of lambda
Parameters:
| Name | Type | Description |
|---|---|---|
data |
array | The data from which to compute lambda |
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(static) computeLambdaUMVUE(data)
Compute the Uniformly Minimum Variance Unbiased Estimator of lambda
Parameters:
| Name | Type | Description |
|---|---|---|
data |
array | The data from which to compute the UMVUE lambda estimator |
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cdf()
The cumulative probability distribution function of the parametrised distribution.
- Overrides:
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fitData(data)
Fits distribution to supplied data. Note: defaults to Uniform Min-Variance Unbiased Estimator!
Parameters:
| Name | Type | Description |
|---|---|---|
data |
array | The data to which this distribution will be fitted |
- Overrides:
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isUniquelyDetermined() → {bool}
The distribution is uniquely determined if it has all the parameters it
requires to compute all other quantities of interest.
- Overrides:
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Returns:
- true if this distribution is uniquely determined, false otherwise
- Type
- bool
pdf()
The probability density function of the parametrised distribution.
- Overrides:
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setLambda(lambda)
Parameters:
| Name | Type | Description |
|---|---|---|
lambda |
float | The lambda with which to parametrise this distribution |
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