tscount v1.4.2

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Analysis of Count Time Series

Likelihood-based methods for model fitting and assessment, prediction and intervention analysis of count time series following generalized linear models are provided. Models with the identity and with the logarithmic link function are allowed. The conditional distribution can be Poisson or Negative Binomial.

Functions in tscount

Name Description
marcal Predictive Model Assessment with a Marginal Calibration Plot
plot.interv_multiple Plot for Iterative Intervention Detection Procedure for Count Time Series following Generalised Linear Models
residuals.tsglm Residuals of a Generalised Linear Model for Time Series of Counts
invertinfo Compute a Covariance Matrix from a Fisher Information Matrix
interv_multiple.tsglm Detecting Multiple Interventions in Count Time Series Following Generalised Linear Models
pit Predictive Model Assessment with a Probability Integral Transform Histogram
predict.tsglm Predicts Method for Time Series of Counts Following Generalised Linear Models
tsglm Count Time Series Following Generalised Linear Models
measles Measles Infections Time Series
plot.interv_detect Plot Test Statistic of Intervention Detection Procedure for Count Time Series Following Generalised Linear Models
summary.tsglm Summarising Fits of Count Time Series following Generalised Linear Models
interv_test.tsglm Testing for Interventions in Count Time Series Following Generalised Linear Models
scoring Predictive Model Assessment with Proper Scoring Rules
tscount-package Analysis of Count Time Series
plot.tsglm Diagnostic Plots for a Fitted GLM-type Model for Time Series of Counts
tsglm.sim Simulate a Time Series Following a Generalised Linear Model
se.tsglm Standard Errors of a Fitted Generalised Linear Model for Time Series of Counts
countdistr Count Data Distributions
QIC Quasi Information Criterion of a Generalised Linear Model for Time Series of Counts
ingarch.analytical Analytical Mean, Variance and Autocorrelation of an INGARCH Process
influenza Influenza Infections Time Series
ehec EHEC Infections Time Series
ecoli E. coli Infections Time Series
interv_covariate Describing Intervention Effects for Time Series with Deterministic Covariates
campy Campylobacter Infections Time Series
interv_detect.tsglm Detecting an Intervention in Count Time Series Following Generalised Linear Models
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Vignettes of tscount

Name
INLA.RData
bibliography.bib
campy.RData
covariates.RData
distrcoef_n200.RData
distrcoef_size1.RData
qic.RData
seatbelts.RData
tscount-computations.R
tsglm.Rnw
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Last month downloads

Details

Type Package
Date 2020-02-29
License GPL-2 | GPL-3
URL http://tscount.r-forge.r-project.org
ByteCompile true
NeedsCompilation no
LazyData true
Encoding UTF-8
Packaged 2020-02-29 22:42:19 UTC; Tobias
Repository CRAN
Date/Publication 2020-03-02 11:30:02 UTC

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