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A B C D E F G H I K L M N O P Q R S T U V W X Y Z misc
| surveillance-package | 'surveillance': Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic Phenomena |
| abattoir | Abattoir Data |
| add1.twinstim | Stepwise Model Selection by AIC |
| addFormattedXAxis | Formatted Time Axis for '"sts"' Objects |
| addSeason2formula | Function that adds a sine-/cosine formula to an existing formula. |
| aggregate-method | Aggregate an '"sts"' Object Over Time or Across Units |
| aggregate.disProg | Aggregate the observed counts |
| aggregate.hhh4sims | Plot Simulations from '"hhh4"' Models |
| aggregate.hhh4simslist | Plot Simulations from '"hhh4"' Models |
| aggregate.sts | Aggregate an '"sts"' Object Over Time or Across Units |
| AIC.twinSIR | Print, Summary and Extraction Methods for '"twinSIR"' Objects |
| alarms | Generic Functions to Access '"sts"' Slots |
| alarms-method | Class '"sts"' - surveillance time series |
| alarms<- | Generic Functions to Access '"sts"' Slots |
| alarms<--method | Class '"sts"' - surveillance time series |
| algo.bayes | The Bayes System |
| algo.bayes1 | The Bayes System |
| algo.bayes2 | The Bayes System |
| algo.bayes3 | The Bayes System |
| algo.bayesLatestTimepoint | The Bayes System |
| algo.call | Query Transmission to Specified Surveillance Algorithm |
| algo.cdc | The CDC Algorithm |
| algo.cdcLatestTimepoint | The CDC Algorithm |
| algo.compare | Comparison of Specified Surveillance Systems using Quality Values |
| algo.cusum | CUSUM method |
| algo.farrington | Surveillance for Count Time Series Using the Classic Farrington Method |
| algo.farrington.assign.weights | Assign weights to base counts |
| algo.farrington.fitGLM | Fit Poisson GLM of the Farrington procedure for a single time point |
| algo.farrington.fitGLM.fast | Fit Poisson GLM of the Farrington procedure for a single time point |
| algo.farrington.fitGLM.populationOffset | Fit Poisson GLM of the Farrington procedure for a single time point |
| algo.farrington.threshold | Compute prediction interval for a new observation |
| algo.glrnb | Count Data Regression Charts |
| algo.glrpois | Count Data Regression Charts |
| algo.hmm | Hidden Markov Model (HMM) method |
| algo.outbreakP | Semiparametric surveillance of outbreaks |
| algo.quality | Computation of Quality Values for a Surveillance System Result |
| algo.rki | The system used at the RKI |
| algo.rki1 | The system used at the RKI |
| algo.rki2 | The system used at the RKI |
| algo.rki3 | The system used at the RKI |
| algo.rkiLatestTimepoint | The system used at the RKI |
| algo.rogerson | Modified CUSUM method as proposed by Rogerson and Yamada (2004) |
| algo.summary | Summary Table Generation for Several Disease Chains |
| algo.twins | Model fit based on a two-component epidemic model |
| all.equal.hhh4 | Test if Two Model Fits are (Nearly) Equal |
| all.equal.twinstim | Test if Two Model Fits are (Nearly) Equal |
| animate | Generic animation of spatio-temporal objects |
| animate.epidata | Spatio-Temporal Animation of an Epidemic |
| animate.epidataCS | Spatio-Temporal Animation of a Continuous-Time Continuous-Space Epidemic |
| animate.sts | Animated Maps and Time Series of Disease Counts or Incidence |
| animate.summary.epidata | Spatio-Temporal Animation of an Epidemic |
| animate_nowcasts | Animate a sequence of nowcasts |
| anscombe.residuals | Compute Anscombe Residuals |
| arlCusum | Calculation of Average Run Length for discrete CUSUM schemes |
| as.data.frame-method | Class '"sts"' - surveillance time series |
| as.data.frame.sts | Class '"sts"' - surveillance time series |
| as.epidata | Continuous-Time SIR Event History of a Fixed Population |
| as.epidata.data.frame | Continuous-Time SIR Event History of a Fixed Population |
| as.epidata.default | Continuous-Time SIR Event History of a Fixed Population |
| as.epidata.epidataCS | Conversion (aggregation) of '"epidataCS"' to '"epidata"' or '"sts"' |
| as.epidataCS | Continuous Space-Time Marked Point Patterns with Grid-Based Covariates |
| as.hhh4simslist | Plot Simulations from '"hhh4"' Models |
| as.stepfun.epidataCS | Continuous Space-Time Marked Point Patterns with Grid-Based Covariates |
| as.ts.sts | Class '"sts"' - surveillance time series |
| as.xts.sts | Class '"sts"' - surveillance time series |
| at2ndChange | Formatted Time Axis for '"sts"' Objects |
| atChange | Formatted Time Axis for '"sts"' Objects |
| atMedian | Formatted Time Axis for '"sts"' Objects |
| autoplot.sts | Time-Series Plots for '"sts"' Objects Using 'ggplot2' |
| backprojNP | Non-parametric back-projection of incidence cases to exposure cases using a known incubation time as in Becker et al (1991) |
| bayes | Multivariate Surveillance through independent univariate algorithms |
| bestCombination | Partition of a number into two factors |
| boda | Bayesian Outbreak Detection Algorithm (BODA) |
| bodaDelay | Bayesian Outbreak Detection in the Presence of Reporting Delays |
| calc.outbreakP.statistic | Semiparametric surveillance of outbreaks |
| calibrationTest | Calibration Tests for Poisson or Negative Binomial Predictions |
| calibrationTest.default | Calibration Tests for Poisson or Negative Binomial Predictions |
| calibrationTest.hhh4 | Predictive Model Assessment for 'hhh4' Models |
| calibrationTest.oneStepAhead | Predictive Model Assessment for 'hhh4' Models |
| campyDE | Campylobacteriosis and Absolute Humidity in Germany 2002-2011 |
| catcusum.LLRcompute | CUSUM detector for time-varying categorical time series |
| categoricalCUSUM | CUSUM detector for time-varying categorical time series |
| checkResidualProcess | Check the residual process of a fitted 'twinSIR' or 'twinstim' |
| clapply | Conditional 'lapply' |
| coef.epitest | Permutation Test for Space-Time Interaction in '"twinstim"' |
| coef.hhh4 | Print, Summary and other Standard Methods for '"hhh4"' Objects |
| coeflist | List Coefficients by Model Component |
| coeflist.default | List Coefficients by Model Component |
| coeflist.hhh4 | Print, Summary and other Standard Methods for '"hhh4"' Objects |
| coeflist.twinstim | Print, Summary and Extraction Methods for '"twinstim"' Objects |
| coefW | Extract Neighbourhood Weights from a Fitted 'hhh4' Model |
| coerce-method | Continuous Space-Time Marked Point Patterns with Grid-Based Covariates |
| coerce-method | Class '"sts"' - surveillance time series |
| coerce-method | Class "stsBP" - a class inheriting from class 'sts' which allows the user to store the results of back-projecting or nowcasting surveillance time series |
| coerce-method | Class "stsNC" - a class inheriting from class 'sts' which allows the user to store the results of back-projecting surveillance time series |
| confint.hhh4 | Print, Summary and other Standard Methods for '"hhh4"' Objects |
| confint.oneStepAhead | Predictive Model Assessment for 'hhh4' Models |
| control | Generic Functions to Access '"sts"' Slots |
| control-method | Class '"sts"' - surveillance time series |
| control<- | Generic Functions to Access '"sts"' Slots |
| control<--method | Class '"sts"' - surveillance time series |
| create.disProg | Creating an object of class disProg |
| cusum | Multivariate Surveillance through independent univariate algorithms |
| delayCDF | Class "stsNC" - a class inheriting from class 'sts' which allows the user to store the results of back-projecting surveillance time series |
| delayCDF-method | Class "stsNC" - a class inheriting from class 'sts' which allows the user to store the results of back-projecting surveillance time series |
| deleval | Surgical Failures Data |
| dim-method | Class '"sts"' - surveillance time series |
| dimnames-method | Class '"sts"' - surveillance time series |
| discpoly | Polygonal Approximation of a Disc/Circle |
| disProg2sts | Convert disProg object to sts and vice versa |
| drop1.twinstim | Stepwise Model Selection by AIC |
| dss | Proper Scoring Rules for Poisson or Negative Binomial Predictions |
| earsC | Surveillance for a count data time series using the EARS C1, C2 or C3 method and its extensions |
| epidata | Continuous-Time SIR Event History of a Fixed Population |
| epidataCS | Continuous Space-Time Marked Point Patterns with Grid-Based Covariates |
| epidataCS2sts | Conversion (aggregation) of '"epidataCS"' to '"epidata"' or '"sts"' |
| epidataCSplot_space | Plotting the Events of an Epidemic over Time and Space |
| epidataCSplot_time | Plotting the Events of an Epidemic over Time and Space |
| epitest | Permutation Test for Space-Time Interaction in '"twinstim"' |
| epoch | Generic Functions to Access '"sts"' Slots |
| epoch-method | Class '"sts"' - surveillance time series |
| epoch<- | Generic Functions to Access '"sts"' Slots |
| epoch<--method | Class '"sts"' - surveillance time series |
| epochInYear | Class '"sts"' - surveillance time series |
| epochInYear-method | Class '"sts"' - surveillance time series |
| extractAIC.twinSIR | Print, Summary and Extraction Methods for '"twinSIR"' Objects |
| fanplot | Fan Plot of Forecast Distributions |
| farrington | Multivariate Surveillance through independent univariate algorithms |
| farringtonFlexible | Surveillance for Univariate Count Time Series Using an Improved Farrington Method |
| fe | Specify Formulae in a Random Effects HHH Model |
| find.kh | Determine the k and h values in a standard normal setting |
| findH | Find decision interval for given in-control ARL and reference value |
| findK | Find Reference Value |
| fixef | Import from package 'nlme' |
| fixef.hhh4 | Print, Summary and other Standard Methods for '"hhh4"' Objects |
| fluBYBW | Influenza in Southern Germany |
| formatDate | Convert Dates to Character (Including Quarter Strings) |
| formatPval | Pretty p-Value Formatting |
| formula.hhh4 | Print, Summary and other Standard Methods for '"hhh4"' Objects |
| getMaxEV | Plots for Fitted 'hhh4'-models |
| getMaxEV_season | Plots for Fitted 'hhh4'-models |
| getNEweights | Extract Neighbourhood Weights from a Fitted 'hhh4' Model |
| getSourceDists | Continuous Space-Time Marked Point Patterns with Grid-Based Covariates |
| glm_epidataCS | Fit an Endemic-Only 'twinstim' as a Poisson-'glm' |
| glrnb | Multivariate Surveillance through independent univariate algorithms |
| glrpois | Multivariate Surveillance through independent univariate algorithms |
| h1_nrwrp | RKI SurvStat Data |
| ha | Hepatitis A in Berlin |
| ha.sts | Hepatitis A in Berlin |
| hagelloch | 1861 Measles Epidemic in the City of Hagelloch, Germany |
| hagelloch.df | 1861 Measles Epidemic in the City of Hagelloch, Germany |
| head.epidataCS | Continuous Space-Time Marked Point Patterns with Grid-Based Covariates |
| hepatitisA | Hepatitis A in Germany |
| hhh4 | Fitting HHH Models with Random Effects and Neighbourhood Structure |
| husO104Hosp | Hospitalization date for HUS cases of the STEC outbreak in Germany, 2011 |
| hValues | Find decision interval for given in-control ARL and reference value |
| iafplot | Plot the Spatial or Temporal Interaction Function of a 'twimstim' |
| imdepi | Occurrence of Invasive Meningococcal Disease in Germany |
| imdepifit | Example 'twinstim' Fit for the 'imdepi' Data |
| influMen | Influenza and meningococcal infections in Germany, 2001-2006 |
| inside.gpc.poly | Test Whether Points are Inside a '"gpc.poly"' Polygon |
| intensity.twinstim | Plotting Intensities of Infection over Time or Space |
| intensityplot | Plot Paths of Point Process Intensities |
| intensityplot.simEpidata | Plotting Paths of Infection Intensities for 'twinSIR' Models |
| intensityplot.simEpidataCS | Plotting Intensities of Infection over Time or Space |
| intensityplot.twinSIR | Plotting Paths of Infection Intensities for 'twinSIR' Models |
| intensityplot.twinstim | Plotting Intensities of Infection over Time or Space |
| intersectPolyCircle | Intersection of a Polygonal and a Circular Domain |
| intersectPolyCircle.gpc.poly | Intersection of a Polygonal and a Circular Domain |
| intersectPolyCircle.owin | Intersection of a Polygonal and a Circular Domain |
| intersectPolyCircle.SpatialPolygons | Intersection of a Polygonal and a Circular Domain |
| intersperse | Impute Blocks for Extra Stops in '"epidata"' Objects |
| isoWeekYear | Find ISO Week and Year of Date Objects |
| k1 | RKI SurvStat Data |
| knox | Knox Test for Space-Time Interaction |
| ks.plot.unif | Plot the ECDF of a uniform sample with Kolmogorov-Smirnov bounds |
| layout.labels | Layout Items for 'spplot' |
| layout.scalebar | Layout Items for 'spplot' |
| linelist2sts | Convert Dates of Individual Case Reports into a Time Series of Counts |
| logLik.hhh4 | Print, Summary and other Standard Methods for '"hhh4"' Objects |
| logLik.twinSIR | Print, Summary and Extraction Methods for '"twinSIR"' Objects |
| logLik.twinstim | Print, Summary and Extraction Methods for '"twinstim"' Objects |
| logs | Proper Scoring Rules for Poisson or Negative Binomial Predictions |
| LRCUSUM.runlength | Run length computation of a CUSUM detector |
| m1 | RKI SurvStat Data |
| m2 | RKI SurvStat Data |
| m3 | RKI SurvStat Data |
| m4 | RKI SurvStat Data |
| m5 | RKI SurvStat Data |
| magic.dim | Compute Suitable k1 x k2 Layout for Plotting |
| makeControl | Generate 'control' Settings for an 'hhh4' Model |
| marks | Import from package 'spatstat.geom' |
| marks.epidataCS | Continuous Space-Time Marked Point Patterns with Grid-Based Covariates |
| measles.weser | Measles in the Weser-Ems region of Lower Saxony, Germany, 2001-2002 |
| measlesDE | Measles in the 16 states of Germany |
| measlesWeserEms | Measles in the Weser-Ems region of Lower Saxony, Germany, 2001-2002 |
| meningo.age | Meningococcal infections in France 1985-1995 |
| MMRcoverageDE | MMR coverage levels in the 16 states of Germany |
| momo | Danish 1994-2008 all cause mortality data for six age groups |
| multinomialTS | Generic Functions to Access '"sts"' Slots |
| multinomialTS-method | Class '"sts"' - surveillance time series |
| multinomialTS<- | Generic Functions to Access '"sts"' Slots |
| multinomialTS<--method | Class '"sts"' - surveillance time series |
| multiplicity | Import from package 'spatstat.geom' |
| multiplicity.Spatial | Count Number of Instances of Points |
| n1 | RKI SurvStat Data |
| n2 | RKI SurvStat Data |
| nbOrder | Determine Neighbourhood Order Matrix from Binary Adjacency Matrix |
| neighbourhood | Generic Functions to Access '"sts"' Slots |
| neighbourhood-method | Class '"sts"' - surveillance time series |
| neighbourhood<- | Generic Functions to Access '"sts"' Slots |
| neighbourhood<--method | Class '"sts"' - surveillance time series |
| nobs.epidataCS | Continuous Space-Time Marked Point Patterns with Grid-Based Covariates |
| nobs.hhh4 | Print, Summary and other Standard Methods for '"hhh4"' Objects |
| nobs.twinstim | Print, Summary and Extraction Methods for '"twinstim"' Objects |
| nowcast | Adjust a univariate time series of counts for observed but-not-yet-reported events |
| observed | Generic Functions to Access '"sts"' Slots |
| observed-method | Class '"sts"' - surveillance time series |
| observed<- | Generic Functions to Access '"sts"' Slots |
| observed<--method | Class '"sts"' - surveillance time series |
| oneStepAhead | Predictive Model Assessment for 'hhh4' Models |
| outbreakP | Multivariate Surveillance through independent univariate algorithms |
| pairedbinCUSUM | Paired binary CUSUM and its run-length computation |
| pairedbinCUSUM.LLRcompute | Paired binary CUSUM and its run-length computation |
| pairedbinCUSUM.runlength | Paired binary CUSUM and its run-length computation |
| permutationTest | Monte Carlo Permutation Test for Paired Individual Scores |
| permute.epidataCS | Randomly Permute Time Points or Locations of '"epidataCS"' |
| pit | Non-Randomized Version of the PIT Histogram (for Count Data) |
| pit.default | Non-Randomized Version of the PIT Histogram (for Count Data) |
| pit.hhh4 | Predictive Model Assessment for 'hhh4' Models |
| pit.oneStepAhead | Predictive Model Assessment for 'hhh4' Models |
| plapply | Verbose and Parallel 'lapply' |
| plot-method | Plot-Methods for Surveillance Time-Series Objects |
| plot.atwins | Plot results of a twins model fit |
| plot.disProg | Plot Generation of the Observed and the Defined Outbreak States of a (Multivariate) Time Series |
| plot.disProg.one | Plot Generation of the Observed and the Defined Outbreak States of a (Multivariate) Time Series |
| plot.epidata | Plotting the Evolution of an Epidemic |
| plot.epidataCS | Plotting the Events of an Epidemic over Time and Space |
| plot.epitest | Permutation Test for Space-Time Interaction in '"twinstim"' |
| plot.hhh4 | Plots for Fitted 'hhh4'-models |
| plot.hhh4sims | Plot Simulations from '"hhh4"' Models |
| plot.hhh4simslist | Plot Simulations from '"hhh4"' Models |
| plot.knox | Knox Test for Space-Time Interaction |
| plot.oneStepAhead | Predictive Model Assessment for 'hhh4' Models |
| plot.profile.twinSIR | Profile Likelihood Computation and Confidence Intervals |
| plot.stKtest | Diggle et al (1995) K-function test for space-time clustering |
| plot.sts | Plot-Methods for Surveillance Time-Series Objects |
| plot.summary.epidata | Plotting the Evolution of an Epidemic |
| plot.survRes | Plot a survRes object |
| plot.survRes.one | Plot a survRes object |
| plot.twinSIR | Plotting Paths of Infection Intensities for 'twinSIR' Models |
| plot.twinstim | Plot methods for fitted 'twinstim"s |
| plotHHH4sims_fan | Plot Simulations from '"hhh4"' Models |
| plotHHH4sims_size | Plot Simulations from '"hhh4"' Models |
| plotHHH4sims_time | Plot Simulations from '"hhh4"' Models |
| plotHHH4_fitted | Plots for Fitted 'hhh4'-models |
| plotHHH4_fitted1 | Plots for Fitted 'hhh4'-models |
| plotHHH4_maps | Plots for Fitted 'hhh4'-models |
| plotHHH4_maxEV | Plots for Fitted 'hhh4'-models |
| plotHHH4_neweights | Plots for Fitted 'hhh4'-models |
| plotHHH4_ri | Plots for Fitted 'hhh4'-models |
| plotHHH4_season | Plots for Fitted 'hhh4'-models |
| poly2adjmat | Derive Adjacency Structure of '"SpatialPolygons"' |
| polyAtBorder | Indicate Polygons at the Border |
| population | Generic Functions to Access '"sts"' Slots |
| population-method | Class '"sts"' - surveillance time series |
| population<- | Generic Functions to Access '"sts"' Slots |
| population<--method | Class '"sts"' - surveillance time series |
| predict.hhh4 | Predictions from a 'hhh4' Model |
| predint | Class "stsNC" - a class inheriting from class 'sts' which allows the user to store the results of back-projecting surveillance time series |
| predint-method | Class "stsNC" - a class inheriting from class 'sts' which allows the user to store the results of back-projecting surveillance time series |
| primeFactors | Prime Number Factorization |
| print.algoQV | Print Quality Value Object |
| print.disProg | Creating an object of class disProg |
| print.epidata | Continuous-Time SIR Event History of a Fixed Population |
| print.epidataCS | Continuous Space-Time Marked Point Patterns with Grid-Based Covariates |
| print.hhh4 | Print, Summary and other Standard Methods for '"hhh4"' Objects |
| print.summary.epidata | Summarizing an Epidemic |
| print.summary.epidataCS | Continuous Space-Time Marked Point Patterns with Grid-Based Covariates |
| print.summary.twinSIR | Print, Summary and Extraction Methods for '"twinSIR"' Objects |
| print.summary.twinstim | Print, Summary and Extraction Methods for '"twinstim"' Objects |
| print.twinSIR | Print, Summary and Extraction Methods for '"twinSIR"' Objects |
| print.twinstim | Print, Summary and Extraction Methods for '"twinstim"' Objects |
| profile.twinSIR | Profile Likelihood Computation and Confidence Intervals |
| profile.twinstim | Profile Likelihood Computation and Confidence Intervals for 'twinstim' objects |
| q1_nrwh | RKI SurvStat Data |
| q2 | RKI SurvStat Data |
| qlomax | Deprecated Functions in Package 'surveillance' |
| quantile.oneStepAhead | Predictive Model Assessment for 'hhh4' Models |
| R0 | Computes reproduction numbers from fitted models |
| R0.simEpidataCS | Computes reproduction numbers from fitted models |
| R0.twinstim | Computes reproduction numbers from fitted models |
| ranef | Import from package 'nlme' |
| ranef.hhh4 | Print, Summary and other Standard Methods for '"hhh4"' Objects |
| refvalIdxByDate | Compute indices of reference value using Date class |
| reportingTriangle | Class "stsNC" - a class inheriting from class 'sts' which allows the user to store the results of back-projecting surveillance time series |
| reportingTriangle-method | Class "stsNC" - a class inheriting from class 'sts' which allows the user to store the results of back-projecting surveillance time series |
| reset.surveillance.options | Options of the 'surveillance' Package |
| residuals.hhh4 | Print, Summary and other Standard Methods for '"hhh4"' Objects |
| residuals.simEpidataCS | Extract Cox-Snell-like Residuals of a Fitted Point Process |
| residuals.twinSIR | Extract Cox-Snell-like Residuals of a Fitted Point Process |
| residuals.twinstim | Extract Cox-Snell-like Residuals of a Fitted Point Process |
| ri | Specify Formulae in a Random Effects HHH Model |
| rki | Multivariate Surveillance through independent univariate algorithms |
| rotaBB | Rotavirus cases in Brandenburg, Germany, during 2002-2013 stratified by 5 age categories |
| rps | Proper Scoring Rules for Poisson or Negative Binomial Predictions |
| s1 | RKI SurvStat Data |
| s2 | RKI SurvStat Data |
| s3 | RKI SurvStat Data |
| salmAllOnset | Salmonella cases in Germany 2001-2014 by data of symptoms onset |
| salmHospitalized | Hospitalized Salmonella cases in Germany 2004-2014 |
| salmNewport | Salmonella Newport cases in Germany 2004-2013 |
| salmonella.agona | Salmonella Agona cases in the UK 1990-1995 |
| scale.gpc.poly | Centering and Scaling a '"gpc.poly"' Polygon |
| score | Class "stsNC" - a class inheriting from class 'sts' which allows the user to store the results of back-projecting surveillance time series |
| score-method | Class "stsNC" - a class inheriting from class 'sts' which allows the user to store the results of back-projecting surveillance time series |
| scores | Proper Scoring Rules for Poisson or Negative Binomial Predictions |
| scores.default | Proper Scoring Rules for Poisson or Negative Binomial Predictions |
| scores.hhh4 | Predictive Model Assessment for 'hhh4' Models |
| scores.hhh4sims | Proper Scoring Rules for Simulations from 'hhh4' Models |
| scores.hhh4simslist | Proper Scoring Rules for Simulations from 'hhh4' Models |
| scores.oneStepAhead | Predictive Model Assessment for 'hhh4' Models |
| ses | Proper Scoring Rules for Poisson or Negative Binomial Predictions |
| shadar | Salmonella Hadar cases in Germany 2001-2006 |
| siaf | Spatial Interaction Function Objects |
| siaf.constant | Temporal and Spatial Interaction Functions for 'twinstim' |
| siaf.exponential | Temporal and Spatial Interaction Functions for 'twinstim' |
| siaf.gaussian | Temporal and Spatial Interaction Functions for 'twinstim' |
| siaf.powerlaw | Temporal and Spatial Interaction Functions for 'twinstim' |
| siaf.powerlaw1 | Temporal and Spatial Interaction Functions for 'twinstim' |
| siaf.powerlawL | Temporal and Spatial Interaction Functions for 'twinstim' |
| siaf.step | Temporal and Spatial Interaction Functions for 'twinstim' |
| siaf.student | Temporal and Spatial Interaction Functions for 'twinstim' |
| sim.pointSource | Simulate Point-Source Epidemics |
| sim.seasonalNoise | Generation of Background Noise for Simulated Timeseries |
| simEndemicEvents | Quick Simulation from an Endemic-Only 'twinstim' |
| simEpidata | Simulation of Epidemic Data |
| simEpidataCS | Simulation of a Self-Exciting Spatio-Temporal Point Process |
| simpleR0 | Computes reproduction numbers from fitted models |
| simulate.hhh4 | Simulate '"hhh4"' Count Time Series |
| simulate.twinSIR | Simulation of Epidemic Data |
| simulate.twinstim | Simulation of a Self-Exciting Spatio-Temporal Point Process |
| stateplot | Plotting the Evolution of an Epidemic |
| stcd | Spatio-temporal cluster detection |
| stepComponent | Stepwise Model Selection by AIC |
| stKtest | Diggle et al (1995) K-function test for space-time clustering |
| sts | Class '"sts"' - surveillance time series |
| sts-class | Class '"sts"' - surveillance time series |
| sts2disProg | Convert disProg object to sts and vice versa |
| stsBP-class | Class "stsBP" - a class inheriting from class 'sts' which allows the user to store the results of back-projecting or nowcasting surveillance time series |
| stsNC-class | Class "stsNC" - a class inheriting from class 'sts' which allows the user to store the results of back-projecting surveillance time series |
| stsNClist_animate | Animate a sequence of nowcasts |
| stsNewport | Salmonella Newport cases in Germany 2001-2015 |
| stsplot | Plot-Methods for Surveillance Time-Series Objects |
| stsplot_alarm | Time-Series Plots for '"sts"' Objects |
| stsplot_space | Map of Disease Counts/Incidence accumulated over a Given Period |
| stsplot_spacetime | Map of Disease Incidence |
| stsplot_time | Time-Series Plots for '"sts"' Objects |
| stsplot_time1 | Time-Series Plots for '"sts"' Objects |
| sts_creation | Simulate Count Time Series with Outbreaks |
| sts_observation | Create an 'sts' object with a given observation date |
| subset.epidataCS | Continuous Space-Time Marked Point Patterns with Grid-Based Covariates |
| summary.epidata | Summarizing an Epidemic |
| summary.epidataCS | Continuous Space-Time Marked Point Patterns with Grid-Based Covariates |
| summary.hhh4 | Print, Summary and other Standard Methods for '"hhh4"' Objects |
| summary.twinSIR | Print, Summary and Extraction Methods for '"twinSIR"' Objects |
| summary.twinstim | Print, Summary and Extraction Methods for '"twinstim"' Objects |
| surveillance | 'surveillance': Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic Phenomena |
| surveillance-deprecated | Deprecated Functions in Package 'surveillance' |
| surveillance.options | Options of the 'surveillance' Package |
| tail.epidataCS | Continuous Space-Time Marked Point Patterns with Grid-Based Covariates |
| tiaf | Temporal Interaction Function Objects |
| tiaf.constant | Temporal and Spatial Interaction Functions for 'twinstim' |
| tiaf.exponential | Temporal and Spatial Interaction Functions for 'twinstim' |
| tiaf.step | Temporal and Spatial Interaction Functions for 'twinstim' |
| tidy.sts | Convert an '"sts"' Object to a Data Frame in Long (Tidy) Format |
| toLatex-method | 'toLatex'-Method for '"sts"' Objects |
| toLatex.knox | Knox Test for Space-Time Interaction |
| toLatex.sts | 'toLatex'-Method for '"sts"' Objects |
| toLatex.summary.twinstim | Print, Summary and Extraction Methods for '"twinstim"' Objects |
| twinSIR | Fit an Additive-Multiplicative Intensity Model for SIR Data |
| twinstim | Fit a Two-Component Spatio-Temporal Point Process Model |
| unionSpatialPolygons | Compute the Unary Union of '"SpatialPolygons"' |
| untie | Randomly Break Ties in Data |
| untie.default | Randomly Break Ties in Data |
| untie.epidataCS | Randomly Break Ties in Data |
| untie.matrix | Randomly Break Ties in Data |
| update.epidata | Continuous-Time SIR Event History of a Fixed Population |
| update.epidataCS | Update method for '"epidataCS"' |
| update.hhh4 | 'update' a fitted '"hhh4"' model |
| update.twinstim | 'update'-method for '"twinstim"' |
| upperbound | Generic Functions to Access '"sts"' Slots |
| upperbound-method | Class '"sts"' - surveillance time series |
| upperbound<- | Generic Functions to Access '"sts"' Slots |
| upperbound<--method | Class '"sts"' - surveillance time series |
| vcov.hhh4 | Print, Summary and other Standard Methods for '"hhh4"' Objects |
| vcov.twinSIR | Print, Summary and Extraction Methods for '"twinSIR"' Objects |
| vcov.twinstim | Print, Summary and Extraction Methods for '"twinstim"' Objects |
| wrap.algo | Multivariate Surveillance through independent univariate algorithms |
| W_np | Power-Law and Nonparametric Neighbourhood Weights for 'hhh4'-Models |
| W_powerlaw | Power-Law and Nonparametric Neighbourhood Weights for 'hhh4'-Models |
| xtable.algoQV | Xtable quality value object |
| xtable.summary.twinstim | Print, Summary and Extraction Methods for '"twinstim"' Objects |
| xtable.twinstim | Print, Summary and Extraction Methods for '"twinstim"' Objects |
| year | Class '"sts"' - surveillance time series |
| year-method | Class '"sts"' - surveillance time series |
| zetaweights | Power-Law Weights According to Neighbourhood Order |
| [-method | Subsetting '"sts"' Objects |
| [.epidata | Continuous-Time SIR Event History of a Fixed Population |
| [.epidataCS | Continuous Space-Time Marked Point Patterns with Grid-Based Covariates |