Recent Developments in Statistical Inference and Data Analysis.

Recent developments in the online distribution and consumption of audio-visual content have brought relevant changes to the transnational flow of content. Thus, the need for a theoretical and methodological rejuvenation of flows research has been signalled. The aim of the present study is to analyse the different flow studies throughout time, following a series of parameters such as research question, methodology and scale of study. This article is a systematic literature review of 30 flow studies on film and television programmes, published between 1974 and 2014. The methods used by the studies are brought into focus and discussed thoroughly, in light of the method of data collection, the type of data used and the method of data analysis. Main findings show an evolution towards more detailed research, to include more contextual factors, an increased use of secondary data, as well as more focused regional and comparative studies.

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Empowering Advanced Driver-Assistance Systems from Topological Data Analysis

Mathematics ◽

10.3390/math9060634 ◽

2021 ◽

Vol 9 (6) ◽

pp. 634

Author(s):

Tarek Frahi ◽

Francisco Chinesta ◽

Antonio Falcó ◽

Alberto Badias ◽

Elias Cueto ◽

...

Keyword(s):

Data Analysis ◽

The State ◽

Sensor Data ◽

Topological Data Analysis ◽

Motion Sensors ◽

Driver Assistance Systems ◽

The Road ◽

Topological Features ◽

Recent Developments ◽

Topological Data

We are interested in evaluating the state of drivers to determine whether they are attentive to the road or not by using motion sensor data collected from car driving experiments. That is, our goal is to design a predictive model that can estimate the state of drivers given the data collected from motion sensors. For that purpose, we leverage recent developments in topological data analysis (TDA) to analyze and transform the data coming from sensor time series and build a machine learning model based on the topological features extracted with the TDA. We provide some experiments showing that our model proves to be accurate in the identification of the state of the user, predicting whether they are relaxed or tense.

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Recent Developments in Chromatographic Fingerprints from Herbal Products: Set-Up and Data Analysis

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/138620710793360284 ◽

2010 ◽

Vol 13 (10) ◽

pp. 900-922 ◽

Cited By ~ 31

Author(s):

Goedele Alaerts ◽

Bieke Dejaegher ◽

Johanna Smeyers-Verbeke ◽

Yvan Vander Heyden

Keyword(s):

Data Analysis ◽

Herbal Products ◽

Chromatographic Fingerprints ◽

Recent Developments ◽

Set Up

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Statistical analysis of the item-count technique using Stata

The Stata Journal Promoting communications on statistics and Stata ◽

10.1177/1536867x19854018 ◽

2019 ◽

Vol 19 (2) ◽

pp. 390-434

Author(s):

Chi-lin Tsai

Keyword(s):

Data Analysis ◽

Statistical Analysis ◽

Count Data ◽

Profile Likelihood ◽

Likelihood Estimation ◽

Great Flexibility ◽

Recent Developments ◽

List Experiment ◽

Experiment Technique ◽

Item Count Technique

In this article, I review recent developments of the item-count technique (also known as the unmatched-count or list-experiment technique) and introduce a new package, kict, for statistical analysis of the item-count data. This package contains four commands: kict deff performs a diagnostic test to detect the violation of an assumption underlying the item-count technique. kict ls and kict ml perform least-squares estimation and maximum likelihood estimation, respectively. Each encompasses a number of estimators, offering great flexibility for data analysis. kict pfci is a postestimation command for producing confidence intervals with better coverage based on profile likelihood. The development of the item-count technique is still ongoing. I will continue to update the kict package accordingly.

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