**Statistics Seminar****（****2018-03****）**

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**Topic:** Case studies on functional control charts and atmospheric profiles uncertainty

**Speaker:** Alessandro Fassò, University of Bergamo, Italy

**Time: **Thursday, March 29, 15:15-16:15

**Place: **Room 217, Guanghua Building 2

**Abstract:**

In the last decade, the analysis of data that are not vectors but functional objects is having an increasing spread in modern statistics, which has to face more complex data objects.

The first case study is motivated by a multiple profile monitoring problem: the health monitoring of a steam sterilizer during its life cycle. Indeed, each sterilization run gives several profiles related to machine health and degradation of the steam sterilizer during its life cycle modifies profile curvature in an unpredictable way. Hence the need for a control chart capable of monitoring multiple sterilization profiles during the sterilizer life cycle.

For covering this kind of problems, we introduce general functional EWMA control charts. When functional data to be monitored are smooth enough to be representable by a finite dimensional basis, a particular version of these functional EWMAs is shown to be a multivariate EWMA applied to basis coefficients. Hence it is called f-EWMA for monitoring single profiles and f-MEWMA for multiple profiles. Control limits and control chart performance are assessed on Monte Carlo simulations.

The second case study is related to the measurement uncertainty of atmospheric profiles obtained by remote sensing and radiosoundings, which is crucial in climate change studies. In this frame, some modelling issues related to functional data representation of temperature profiles are discussed.

In particular, co-location mismatch of a satellite profile and a radiosonde profile is discussed. The objective is the assessment of the vertical smoothing mismatch uncertainty related to this profile comparison. To see this, radiosondes are harmonised to match the satellite data in a two steps procedure, which is based on the maximum likelihood approach and exploits the measurement uncertainties in a natural way. At the first step, radiosonde profiles are transformed into continuous functions using splines. At the second step, radiosonde profiles are harmonized by considering weighting functions based on the generalised extreme values probability density function with parameters depending on altitude. The variation between harmonised and non-harmonised radiosonde is then informative on vertical smoothing mismatch.

**Introduction:**

Alessandro Fassò is full professor of Statistics from 2000 at the University of Bergamo. President of The International Environmetrics Society (TIES) (2017-2019). Founder and previous Coordinator (2013-2015) of GRASPA the permanent working group for environmental statistics of the Italian Statistical Society (SIS). Member of the Council of the International Statistical Institute (ISI) (2013-2017). Member of WG-GRUAN, the Working Group on Atmospheric Reference Observations, promoted by the World Meterological Organization (www.wmo.int).

He is Editor of the Chilean Journal of Statistics. Associate Editor of Stochastic Environmental Research and Risk Analysis (SERRA) and of Advances in Statistical Analysis (AStA). Guest Editor of Environmetrics (2007), Advances in Statistical Analysis (AStA, 2013), Stochastic Environmental Research and Risk Analysis (SERRA, 2015) and Statistical Methods & Applications (SMAP, 2016).

He is Author of more than hundred papers, mainly on statistical methods and applications to environmetrics, air quality, climate variables, sensitivity analysis of environmental models, environmental time-series, spatio-temporal data, stochastic monitoring, structural and geotechnical surveillance, industrial statistics, quality control and financial time series analysis.

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