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 surveillance: Temporal and SpatioTemporal Modeling and Monitoring of Epidemic Phenomena
 algo.quality: Computation of Quality Values for a Surveillance System...
Computation of Quality Values for a Surveillance System Result
Description
Computation of the quality values for a surveillance System output.
Usage
1  algo.quality(sts, penalty = 20)

Arguments
sts 
object of class 
penalty 
the maximal penalty for the lag 
Details
The lag is defined as follows:
In the state chain just the beginnings of an outbreak chain (outbreaks directly
following each other) are considered. In the alarm chain, the range from the beginning
of an outbreak until min(next outbreak beginning,\code{penalty}) timepoints is considered. The penalty
timepoints were
chosen, to provide an upper bound on the penalty for not discovering an outbreak. Now the difference between the first alarm by the system and the defined beginning is denoted “the lag” Additionally outbreaks found by the system are not
punished. At the end, the mean of the lags for every outbreak chain is returned
as summary lag.
Value
list of quality values 

See Also
algo.compare
Examples
1 2 3 4 5 6 7 8 9 10  # Create a test object
disProgObj < sim.pointSource(p = 0.99, r = 0.5, length = 200, A = 1,
alpha = 1, beta = 0, phi = 0,
frequency = 1, state = NULL, K = 1.7)
# Let this object be tested from rki1
survResObj < algo.rki1(disProgObj, control = list(range = 50:200))
# Compute the quality values
algo.quality(survResObj)

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 abattoir: Abattoir Data
 addFormattedXAxis: Formatted Time Axis for '"sts"' Objects
 addSeason2formula: Function that adds a sine/cosine formula to an existing...
 aggregate.disProg: Aggregate the observed counts
 algo.bayes: The Bayes System
 algo.call: Query Transmission to Specified Surveillance Algorithm
 algo.cdc: The CDC Algorithm
 algo.compare: Comparison of Specified Surveillance Systems using Quality...
 algo.cusum: CUSUM method
 algo.farrington: Surveillance for a count data time series using the...
 algo.farrington.assign.weights: Assign weights to base counts
 algo.farrington.fitGLM: Fit the Poisson GLM of the Farrington procedure for a single...
 algo.farrington.threshold: Compute prediction interval for a new observation
 algo.glrnb: Count Data Regression Charts
 algo.hhh: Fit a Classical HHH Model (DEPRECATED)
 algo.hhh.grid: Fit a Classical HHH Model (DEPRECATED) with Varying Start...
 algo.hmm: Hidden Markov Model (HMM) method
 algo.outbreakP: Semiparametric surveillance of outbreaks
 algo.quality: Computation of Quality Values for a Surveillance System...
 algo.rki: The system used at the RKI
 algo.rogerson: Modified CUSUM method as proposed by Rogerson and Yamada...
 algo.summary: Summary Table Generation for Several Disease Chains
 algo.twins: Model fit based on a twocomponent epidemic model
 all.equal: Test if Two Model Fits are (Nearly) Equal
 animate: Generic animation of spatiotemporal objects
 anscombe.residuals: Compute Anscombe Residuals
 arlCusum: Calculation of Average Run Length for discrete CUSUM schemes
 backprojNP: Nonparametric backprojection of incidence cases to exposure...
 bestCombination: Partition of a number into two factors
 boda: Surveillance for an univariate count data time series using...
 bodaDelay: Bayesian Outbreak Detection in the Presence of Reporting...
 calibration: Calibration Test for Poisson or Negative Binomial Predictions
 campyDE: Cases of Campylobacteriosis and Absolute Humidity in Germany...
 categoricalCUSUM: CUSUM detector for timevarying categorical time series
 checkResidualProcess: Check the residual process of a fitted 'twinSIR' or...
 coeflist: List Coefficients by Model Component
 compMatrix.writeTable: Latex Table Generation
 correct53to52: Data Correction from 53 to 52 weeks
 create.disProg: Creating an object of class disProg
 create.grid: Create a Matrix of Initial Values for 'algo.hhh.grid'
 deleval: Surgical failures data
 discpoly: Polygonal Approximation of a Disc/Circle
 disProg2sts: Convert disProg object to sts and vice versa
 earsC: Surveillance for a count data time series using the EARS C1,...
 enlargeData: Data Enlargement
 epidata: ContinuousTime SIR Event History of a Fixed Population
 epidata_animate: SpatioTemporal Animation of an Epidemic
 epidataCS: Continuous SpaceTime Marked Point Patterns with GridBased...
 epidataCS_aggregate: Conversion (aggregation) of '"epidataCS"' to '"epidata"' or...
 epidataCS_animate: SpatioTemporal Animation of a ContinuousTime...
 epidataCS_permute: Randomly Permute Time Points or Locations of '"epidataCS"'
 epidataCS_plot: Plotting the Events of an Epidemic over Time and Space
 epidataCS_update: Update method for '"epidataCS"'
 epidata_intersperse: Impute Blocks for Extra Stops in '"epidata"' Objects
 epidata_plot: Plotting the Evolution of an Epidemic
 epidata_summary: Summarizing an Epidemic
 estimateGLRNbHook: Hook function for incontrol mean estimation
 farringtonFlexible: Surveillance for an univariate count data time series using...
 findH: Find decision interval for given incontrol ARL and reference...
 findK: Find reference value
 find.kh: Determine the k and h values in a standard normal setting
 fluBYBW: Influenza in Southern Germany
 formatPval: Pretty pValue Formatting
 glm_epidataCS: Fit an EndemicOnly 'twinstim' as a Poisson'glm'
 ha: Hepatitis A in Berlin
 hagelloch: 1861 Measles Epidemic in the City of Hagelloch, Germany
 hepatitisA: Hepatitis A in Germany
 hhh4: Fitting HHH Models with Random Effects and Neighbourhood...
 hhh4_calibration: Test Calibration of a 'hhh4' Model
 hhh4_formula: Specify Formulae in a Random Effects HHH Model
 hhh4_methods: Print, Summary and other Standard Methods for '"hhh4"'...
 hhh4_plot: Plots for Fitted 'hhh4'models
 hhh4_predict: Predictions from a 'hhh4' Model
 hhh4_simulate: Simulate '"hhh4"' Count Time Series
 hhh4_simulate_plot: Summarize Simulations from '"hhh4"' Models
 hhh4_update: 'update' a fitted '"hhh4"' model
 hhh4_validation: Predictive Model Assessment for 'hhh4' Models
 hhh4_W: PowerLaw and Nonparametric Neighbourhood Weights for...
 husO104Hosp: Hospitalization date for HUS cases of the STEC outbreak in...
 imdepi: Occurrence of Invasive Meningococcal Disease in Germany
 influMen: Influenza and meningococcal infections in Germany, 20012006
 inside.gpc.poly: Test Whether Points are Inside a '"gpc.poly"' Polygon
 intensityplot: Plot Paths of Point Process Intensities
 intersectPolyCircle: Intersection of a Polygonal and a Circular Domain
 isoWeekYear: Find ISO week and ISO year of a vector of Date objects on...
 isScalar: Checks if the Argument is Scalar
 knox: Knox Test for SpaceTime Interaction
 ks.plot.unif: Plot the ECDF of a uniform sample with KolmogorovSmirnov...
 layout.labels: Layout Items for 'spplot'
 linelist2sts: Convert individual case information based on dates into an...
 loglikelihood: Calculation of the loglikelihood needed in algo.hhh
 LRCUSUM.runlength: Run length computation of a CUSUM detector
 m1: RKI SurvStat Data
 magic.dim: Returns a suitable k1 x k2 for plotting the disProgObj
 make.design: Create the design matrices
 makePlot: Plot Generation
 marks: Import from package 'spatstat'
 meanResponse: Calculate mean response needed in algo.hhh
 measlesDE: Measles in the 16 states of Germany
 measles.weser: Measles in the WeserEms region of Lower Saxony, Germany,...
 meningo.age: Meningococcal infections in France 19851995
 MMRcoverageDE: MMR coverage levels in the 16 states of Germany
 momo: Danish 19942008 all cause mortality data for six age groups
 multiplicity: Import from package 'spatstat'
 multiplicity.Spatial: Count Number of Instances of Points
 nbOrder: Determine Neighbourhood Order Matrix from Binary Adjacency...
 nowcast: Adjust a univariate time series of counts for observed...
 pairedbinCUSUM: Paired binary CUSUM and its runlength computation
 permutationTest: Monte Carlo Permutation Test for Paired Individual Scores
 pit: NonRandomized Version of the PIT Histogram (for Count Data)
 plapply: Verbose and Parallel 'lapply'
 plot.atwins: Plot results of a twins model fit
 plot.disProg: Plot Generation of the Observed and the defined Outbreak...
 plot.survRes: Plot a survRes object
 poly2adjmat: Derive Adjacency Structure of '"SpatialPolygons"'
 polyAtBorder: Indicate Polygons at the Border
 predict.ah: Predictions from a HHH model
 primeFactors: Prime number factorization
 print.algoQV: Print quality value object
 qlomax: Quantile Function of the Lomax Distribution
 R0: Computes reproduction numbers from fitted models
 ranef: Import from package 'nlme'
 readData: Reading of Disease Data
 refvalIdxByDate: Compute indices of reference value using Date class
 residuals.ah: Residuals from a HHH model
 residualsCT: Extract CoxSnelllike Residuals of a Fitted Point Process
 rotaBB: Rotavirus cases in Brandenburg, Germany, during 20022013...
 runifdisc: Sample Points Uniformly on a Disc
 salmAllOnset: Salmonella cases in Germany 20012014 by data of symptoms...
 salmHospitalized: Hospitalized Salmonella cases in Germany 20042014
 salmNewport: Salmonella Newport cases in Germany 20042013
 salmonella.agona: Salmonella Agona cases in the UK 19901995
 scale.gpc.poly: Centering and Scaling a '"gpc.poly"' Polygon
 shadar: Salmonella Hadar cases in Germany 20012006
 simHHH: Simulates data based on the model proposed by Held et. al...
 sim.pointSource: Simulate PointSource Epidemics
 sim.seasonalNoise: Generation of Background Noise for Simulated Timeseries
 stcd: Spatiotemporal cluster detection
 stK: Diggle et al (1995) Kfunction test for spacetime clustering
 stsAggregate: Aggregate an '"sts"' Object Over Time or Across Units
 sts_animate: Animated Maps and Time Series of Disease Counts or Incidence
 stsBPclass: Class "stsBP"  a class inheriting from class 'sts' which...
 stsclass: Class '"sts"'  surveillance time series
 sts_creation: Function for simulating a time series
 stsNCclass: Class "stsNC"  a class inheriting from class 'sts' which...
 stsNClist_animate: Animate a sequence of nowcasts
 stsNewport: Salmonella Newport cases in Germany 20042013
 sts_observation: Function for creating a stsobject with a given observation...
 stsplot: PlotMethods for Surveillance TimeSeries Objects
 stsplot_space: Map of Disease Counts/Incidence accumulated over a Given...
 stsplot_spacetime: Map of Disease Incidence
 stsplot_time: TimeSeries Plots for '"sts"' Objects
 stsSlots: Generic functions to access '"sts"' slots
 stsXtrct: Extraction and Subsetting of '"sts"' Objects
 sumNeighbours: Calculates the sum of counts of adjacent areas
 surveillance.options: Options of the 'surveillance' Package
 surveillancepackage: \Sexpr[stage=build]{(meta <...
 test: Print xtable for several diseases and the summary
 testSim: Print xtable for a Simulated Disease and the Summary
 toFileDisProg: Writing of Disease Data
 toLatex.sts: 'toLatex'Method for '"sts"' Objects
 twinSIR: Fit an AdditiveMultiplicative Intensity Model for SIR Data
 twinSIR_cox: Identify Endemic Components in an Intensity Model
 twinSIR_exData: Toy Data for 'twinSIR'
 twinSIR_intensityplot: Plotting Paths of Infection Intensities for 'twinSIR' Models
 twinSIR_methods: Print, Summary and Extraction Methods for '"twinSIR"' Objects
 twinSIR_profile: Profile Likelihood Computation and Confidence Intervals
 twinSIR_simulation: Simulation of Epidemic Data
 twinstim: Fit a TwoComponent SpatioTemporal Point Process Model
 twinstim_epitest: Permutation Test for SpaceTime Interaction in '"twinstim"'
 twinstim_iaf: Temporal and Spatial Interaction Functions for 'twinstim'
 twinstim_iafplot: Plot the Spatial or Temporal Interaction Function of a...
 twinstim_intensity: Plotting Intensities of Infection over Time or Space
 twinstim_methods: Print, Summary and Extraction Methods for '"twinstim"'...
 twinstim_plot: Plot methods for fitted 'twinstim"s
 twinstim_profile: Profile Likelihood Computation and Confidence Intervals for...
 twinstim_siaf: Spatial Interaction Function Objects
 twinstim_siaf_simulatePC: Simulation from an Isotropic Spatial Kernel via Polar...
 twinstim_simulation: Simulation of a SelfExciting SpatioTemporal Point Process
 twinstim_step: Stepwise Model Selection by AIC
 twinstim_tiaf: Temporal Interaction Function Objects
 twinstim_update: 'update'method for '"twinstim"'
 unionSpatialPolygons: Compute the Unary Union of '"SpatialPolygons"'
 untie: Randomly Break Ties in Data
 wrap.algo: Multivariate Surveillance through independent univariate...
 xtable.algoQV: Xtable quality value object
 zetaweights: PowerLaw Weights According to Neighbourhood Order