In this paper we characterised the data regarding cattle deaths into "on-farm" deaths, reported by agricultural holdings, landless keepers, knackers yard, hunt kennels, markets and on common land (perceived to be culled or diseased cattle) and those occurring at slaughterhouse premises (assumed to be entering the food or animal feed chain).
We now extend this study to further characterise the data generating process of mortality series at the individual ICU level and the impact of autocorrelation upon (i) mortality monitoring using EWMA (exponentially weighted moving average) control charts and (ii) time-series modelling of the data process using residual control charts.
In this study, we aimed to characterise the data currently available from social media networking platforms and to determine if, and how, such data can be tapped for surveillance of two specific safety issues: rosiglitazone and cardiovascular events (i.e. stroke and myocardial infarction), and HPV vaccine and infertility.
To characterise the data for subsequent synthesis, array pre-processing was performed using RMA [11], and for each probeset a maximum-likelihood lognormal distribution was fit to the six normal sample RMA expression measures.
Standard descriptive statistics were used to characterise the data.
The TSP is scored on an ordinal scale and the median and range were therefore used to characterise the data.
Based on visual inspection of PACF and ACF plots, an ARIMA (1,0,2) model best characterised for rosiglitazone data and pioglitazone data was best characterised as an ARIMA (1,0,1).
Tests using the previously characterised E. coli data described in the Data section validated this parameter value: root mean squared error was minimised when 0.30≤ t sim ≤ 0.32.
Our model can be characterised using data from a Kubernetes deployment, and can be exploited for supporting capacity planning and designing Kubernetes-based elastic applications.
Noting that options may be characterised with data of various scale types, the paper introduces a number of different policies for optimality appropriate to the different scale types, and derives closed expressions that implement the various policies.
