tscount v1.3.0

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

Type Package
Date 2016-05-13
License GPL-2 | GPL-3
URL http://tscount.r-forge.r-project.org
ByteCompile true
NeedsCompilation no
LazyData true
Encoding UTF-8
Packaged 2016-05-13 16:50:30 UTC; liboschik
Repository CRAN
Date/Publication 2016-05-13 19:30:24

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