A B C D E F G H I K L M N O P Q R S T U W X Y misc
surveillance-package | Outbreak detection algorithms for surveillance data |
abattoir | Abattoir Data |
aggregate,sts,ANY,ANY-method | Aggregate the the series of an sts object |
aggregate,sts-method | Aggregate the the series of an sts object |
aggregate.disProg | Aggregate the observed counts |
alarms | Methods |
alarms,sts-method | Class "sts" - surveillance time series |
alarms-methods | Methods |
alarms<- | Methods |
alarms<-,sts-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 Systems |
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 a time series using the Farrington procedure. |
algo.farrington.assign.weights | Assign weights to base counts |
algo.farrington.fitGLM | Fit the Poisson GLM of the Farrington procedure for a single time point |
algo.farrington.threshold | Threshold computations using a two sided confidence interval |
algo.glrnb | Cound data regression charts |
algo.glrpois | Poisson regression charts |
algo.hhh | Model fit based on the Held, Hoehle, Hofman paper |
algo.hhh.grid | Function to try multiple starting values |
algo.hmm | Hidden Markov Model (HMM) method |
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 |
anscombe.residuals | Compute Anscombe residuals |
arlCusum | Calculation of Average Run Length for discrete CUSUM schemes |
as.data.frame,sts-method | Class "sts" - surveillance time series |
bayes | Multivariate Surveillance through independent univariate algorithms |
bestCombination | Partition of a number into two factors |
catcusum.LLRcompute | CUSUM detector for time-varying categorical time series |
categoricalCUSUM | CUSUM detector for time-varying categorical time series |
cdc | Multivariate Surveillance through independent univariate algorithms |
CIdata | Confidence-Interval for the Mean of the Poisson Distribution |
coef.ah | Model fit based on the Held, Hoehle, Hofman paper |
coef.ahg | Function to try multiple starting values |
colnames,sts,missing,missing-method | Class "sts" - surveillance time series |
compMatrix.writeTable | Latex Table Generation |
control | Methods |
control,sts-method | Class "sts" - surveillance time series |
control-methods | Methods |
control<- | Methods |
control<-,sts-method | Class "sts" - surveillance time series |
correct53to52 | Data Correction from 53 to 52 weeks |
create.disProg | Creating an object of class disProg |
create.grid | Computes a matrix of initial values |
cusum | Multivariate Surveillance through independent univariate algorithms |
deleval | Surgical failures data |
dim,sts-method | Class "sts" - surveillance time series |
disProg2sts | Convert disProg object to sts and vice versa |
enlargeData | Data Enlargement |
epoch | Methods |
epoch,sts-method | Class "sts" - surveillance time series |
epoch-methods | Methods |
epoch<- | Methods |
epoch<-,sts-method | Class "sts" - surveillance time series |
epochInYear | Methods |
epochInYear,sts-method | Class "sts" - surveillance time series |
epochInYear-methods | Methods |
epochInYear<- | Methods |
estimateGLRNbHook | Hook function for in-control mean estimation |
estimateGLRPoisHook | Hook function for in-control mean estimation |
farrington | Multivariate Surveillance through independent univariate algorithms |
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 |
glrnb | Multivariate Surveillance through independent univariate algorithms |
glrpois | Multivariate Surveillance through independent univariate algorithms |
h1_nrwrp | RKI SurvStat Data |
ha | Hepatitis A in Berlin |
hepatitisA | Hepatitis A in Germany |
hmm | Multivariate Surveillance through independent univariate algorithms |
hValues | Find decision interval for given in-control ARL and reference value |
influMen | Influenza and meningococcal infections in Germany, 2001-2006 |
initialize,sts-method | Class "sts" - surveillance time series |
k1 | RKI SurvStat Data |
LLR.fun | Run length computation of a CUSUM detector |
loglikelihood | Calculation of the loglikelihood needed in algo.hhh |
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 | Returns a suitable k1 x k2 for plotting the disProgObj |
make.design | Create the design matrices |
makePlot | Plot Generation |
meanResponse | Calculate mean response needed in algo.hhh |
measles.weser | Measles epidemics in Lower Saxony in 2001-2002 |
meningo.age | Meningococcal infections in France 1985-1995 |
momo | Danish 1994-2008 all cause mortality data for six age groups |
n1 | RKI SurvStat Data |
n2 | RKI SurvStat Data |
ncol,sts-method | Class "sts" - surveillance time series |
nrow,sts-method | Class "sts" - surveillance time series |
observed | Methods |
observed,sts-method | Class "sts" - surveillance time series |
observed-methods | Methods |
observed<- | Methods |
observed<-,sts-method | Class "sts" - surveillance time series |
obsinyear | ~~ Methods for Function obsinyear ~~ |
obsinyear,sts-method | ~~ Methods for Function obsinyear ~~ |
obsinyear-methods | ~~ Methods for Function obsinyear ~~ |
outcomeFunStandard | Run length computation of a CUSUM detector |
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 |
plot | Display Methods for Surveillance Time-Series Objects |
plot,sts,missing-method | Display 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.sts.alarm | Display Methods for Surveillance Time-Series Objects |
plot.sts.spacetime | Display Methods for Surveillance Time-Series Objects |
plot.sts.time | Display Methods for Surveillance Time-Series Objects |
plot.sts.time.one | Display Methods for Surveillance Time-Series Objects |
plot.survRes | Plot a survRes object |
plot.survRes.one | Plot a survRes object |
population | Methods |
population,sts-method | Class "sts" - surveillance time series |
population-methods | Methods |
population<- | Methods |
population<-,sts-method | Class "sts" - surveillance time series |
predict.ah | Predictions from a HHH model |
predict.ahg | Predictions from a HHH model |
primeFactors | Prime number factorization |
print.ah | Model fit based on the Held, Hoehle, Hofman paper |
print.ahg | Function to try multiple starting values |
print.algoQV | Print quality value object |
q1_nrwh | RKI SurvStat Data |
q2 | RKI SurvStat Data |
readData | Reading of Disease Data |
refvalIdxByDate | Compute indices of reference value using Date class |
residuals.ah | Residuals from a HHH model |
residuals.ahg | Residuals from a HHH model |
rki | Multivariate Surveillance through independent univariate algorithms |
rogerson | Multivariate Surveillance through independent univariate algorithms |
s1 | RKI SurvStat Data |
s2 | RKI SurvStat Data |
s3 | RKI SurvStat Data |
salmonella.agona | Salmonella Agona cases in the UK 1990-1995 |
shadar | Salmonella Hadar cases in Germany 2001-2006 |
show,sts-method | Display Methods for Surveillance Time-Series Objects |
sim.pointSource | Generation of Simulated Point Source Epidemy |
sim.seasonalNoise | Generation of Background Noise for Simulated Timeseries |
simHHH | Simulates data based on the model proposed by Held et. al (2005) |
simHHH.ah | Simulates data based on the model proposed by Held et. al (2005) |
simHHH.default | Simulates data based on the model proposed by Held et. al (2005) |
stcd | Spatio-temporal cluster detection |
sts-class | Class "sts" - surveillance time series |
sts2disProg | Convert disProg object to sts and vice versa |
sumNeighbours | Calculates the sum of counts of adjacent areas |
surveillance | Outbreak detection algorithms for surveillance data |
test | Print xtable for several diseases and the summary |
testSim | Print xtable for a Simulated Disease and the Summary |
toFileDisProg | Writing of Disease Data |
upperbound | Methods |
upperbound,sts-method | Class "sts" - surveillance time series |
upperbound<- | Methods |
upperbound<-,sts-method | Class "sts" - surveillance time series |
wrap.algo | Multivariate Surveillance through independent univariate algorithms |
xtable.algoQV | Xtable quality value object |
year | Methods for Function year |
year,sts-method | Methods for Function year |
year-methods | Methods for Function year |
[,sts,ANY,ANY,ANY-method | Methods for "[": Extraction or Subsetting in Package 'surveillance' |
[,sts-method | Methods for "[": Extraction or Subsetting in Package 'surveillance' |
[-methods | Methods for "[": Extraction or Subsetting in Package 'surveillance' |