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Function simul.dbFD [FD v1.0-12]
keywords
datagen
title
Simulations to Explore Relationships Between Functional Diversity Indices
description
simul.dbFD generates artificial communities of species with artificial functional traits. Different functional diversity (FD) indices are computed from these communities using dbFD to explore their inter-relationships.
Function utilsForExamples [EMCC v1.3]
keywords
datagen
title
The utility function(s) for examples
description
The utility function(s) that are used in the example sections of the exported functions in this package.
Function SimulateMixture [flowClust v3.10.1]
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datagen
title
Random Generation from a t Mixture Model with Box-Cox Transformation
description
This function can be used to generate a sample from a multivariate $t$ mixture model with Box-Cox transformation.
Function Waveforms [tuneR v1.3.3]
keywords
datagen
title
Create Wave Objects of Special Waveforms
description
Create a Wave object of special waveform such as silcence, power law (white, red, pink, ...) noise, sawtooth, sine, square, and pulse.
Function priceFeature [flexclust v1.4-0]
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datagen
title
Artificial 2d Market Segment Data
description
Simple artificial 2-dimensional data to demonstrate clustering for market segmentation. One dimension is the hypothetical feature sophistication (or performance or quality, etc) of a product, the second dimension the price customers are willing to pay for the product.
Function Renext-package [Renext v3.1-0]
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datagen
title
Renewal Method for Extreme Values Extrapolation
description
This package proposes fits and diagnostics for the so-called méthode du renouvellement, an alternative to other "Peaks Over Threshold" (POT) methods. The méthode du renouvellement generalises the classical POT by allowing the excesses over the threshold to follow a probability distribution which can differ from the Generalised Pareto Distribution (GPD). Weibull or gamma excesses are sometimes preferred to GPD excesses. The special case of exponential excesses (which falls in the three families: GPD, Weibull and gamma) has a special interest since it allows exact inference for the (scalar) parameter and for the quantiles form OT data (only). The package allows the joint use of possibly three kinds of data or information. The first kind is classical excesses, or "OT data". It can be completed with two kinds of data resulting from a temporal aggregation, as is often the case for historical data. Both types are optional, and concern periods or blocks that must not overlap nor cross the OT period. MAX data correspond to the case where one knows the $r$ largest observations over each block. The number $r$ may vary across blocks. This kind of data is often called '$r$ largest', or "$r$ Largest Order Statistics" ($r$ LOS). OTS data (for OT Supplementary data) correspond to the case where one knows for each block $b$ all the observations that exceeded a threshold $u[b]$ which is greater (usually much greater) than the main threshold $u$. The number $r[b]$ of such observations can be zero, in which case we may say that $u[b]$ is an unobserved level. A threshold $u[b]$ is sometimes called a perception threshold. Historical data are often available in hydrology (e.g. for river flood discharges, for sea-levels or sea surges) and can concern large periods such as past centuries. An unobserved level can typically be related to a material benchmark. Maximum likelihood estimation is made possible in this context of heterogeneous data. Inference is based on the asymptotic normality of parameter vector estimate and on linearisation ("delta method") for quantiles or parameter functions. The package allows the use of "marked-process observations" data (datetime of event and level) where an interevent analysis can be useful. It also allows the event dates to be unknown and replaced by a much broader block indication, e.g. a year number. The key point is then that the "effective duration" (total duration of observation periods) is known. Event counts for blocks can be used to check the assumption of Poisson-distributed events. The package development was initiated, directed and financed by the french Institut de Radioprotection et de Sûreté Nucléaire (IRSN). The package is a non-academic tool designed for applied analysis on case studies and investigations or comparisons on classical probabilistic models.
Function temperature [VFS v1.0.2]
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title
Generate simulated mean temperature
description
Generates simulated daily temperature minimum and maximum based on parameters derived from daily weather data.
Function rainfall [VFS v1.0.2]
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datagen
title
Generate simulated daily rainfall
description
Generates simulated daily rainfall based on parameters derived from daily weather data.
Function simulateSNPcatResponse [scrime v1.3.5]
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datagen
title
Simulation of SNP Data with Categorical Response
description
Simulates SNP data. Interactions of some of the simulated SNPs are then used to specify a categorical response by level-wise or multinomial logistic regression.
Function simulateSNPglm [scrime v1.3.5]
keywords
datagen
title
Simulation of SNP data
description
Simulates SNP data. Interactions of some of the simulated SNPs are then used to specify either a binary or a quantitative response by a logistic or linear regression model, respectively.