gte_data

<p>
The data are daily failure times of 125 telecommunication systems, including 
their respective censoring 
indicator, installed by the GTE corporation in a pre-specified time period (Kim and Proschan 1991).</p>

datasets

Due to a large quantity of non-Gaussian time series and reliability data, the R-package non-Gaussian state-space with exact marginal likelihood is useful for modeling and forecasting non-Gaussian time series and reliability data via non-Gaussian state-space models with the exact marginal likelihood easily, see Gamerman, Santos and Franco (2013) <doi:10.1111/jtsa.12039> and Santos, Gamerman and Franco (2017) <doi:10.1109/TR.2017.2670142>. The package gives codes for formulating and specifying the non-Gaussian state-space models in the R language. Inferences for the parameters of the model can be made under the classical and Bayesian. Furthermore, prediction, filtering, and smoothing procedures can be used to perform inferences for the latent parameters. Applications include, e.g., count, volatility, piecewise exponential, and software reliability data.

T. dos Santos

NGSSEML

Non-Gaussian State-Space with Exact Marginal Likelihood

gte_data function

<p>A data frame with 125 rows and 2 variables.</p>

gte_data: Daily failure times of 125 telecommunication systems installed by the GTE

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Examples