Incorporating Statistical Consulting Case Studies in Introductory Time Series Courses

2015 ◽  
Vol 69 (4) ◽  
pp. 387-396 ◽  
Author(s):  
Davit Khachatryan
Keyword(s):  
Time Series ◽  
Case Studies ◽  
Statistical Consulting

Detecting subtle change from dense Landsat time series: Case studies of mountain pine beetle and spruce beetle disturbance

2021 ◽  
Vol 263 ◽  
pp. 112560
Author(s):  
Su Ye ◽  
John Rogan ◽  
Zhe Zhu ◽  
Todd J. Hawbaker ◽  
Sarah J. Hart ◽  
...  
Keyword(s):  
Time Series ◽  
Case Studies ◽  
Mountain Pine Beetle ◽  
Subtle Change ◽  
Mountain Pine ◽  
Spruce Beetle ◽  
Pine Beetle

Forecasting Demand With Support Vector Regression Technique Incorporating Feature Selection in the Presence of Calendar Effect

2018 ◽  
pp. 302-316 ◽  
Author(s):  
Malek Sarhani ◽  
Abdellatif El Afia
Keyword(s):  
Time Series ◽  
Feature Selection ◽  
Supply Chains ◽  
Support Vector Regression ◽  
Case Studies ◽  
Time Series Forecasting ◽  
Regression Technique ◽  
Support Vector ◽  
Reliable Prediction ◽  
Forecasting Methods

Reliable prediction of future demand is needed to better manage and optimize supply chains. However, a difficulty of forecasting demand arises due to the fact that heterogeneous factors may affect it. Analyzing such data by using classical time series forecasting methods will fail to capture such dependency of factors. This chapter addresses these problems by examining the use of feature selection in forecasting using support vector regression while eliminating the calendar effect using X13-ARIMA-SEATS. The approach is investigated in three different case studies.

scholarly journals Observations of Ash, Ice, and Lightning within Pyrocumulus Clouds Using Polarimetric NEXRAD Radars and the National Lightning Detection Network

2017 ◽  
Vol 145 (12) ◽  
pp. 4899-4910 ◽  
Author(s):  
Kendell T. LaRoche ◽  
Timothy J. Lang
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Case Studies ◽  
Correlation Coefficient ◽  
Convective Cloud ◽  
Past Research ◽  
Polarimetric Radar ◽  
Dual Polarization ◽  
Lightning Detection ◽  
Differential Reflectivity

A pyrocumulus is a convective cloud that can develop over a wildfire. Under certain conditions, pyrocumulus clouds become vertically developed enough to produce lightning. NEXRAD dual-polarization weather radar and upgraded National Lightning Detection Network (NLDN) data were used to analyze 10 case studies of ash plumes and pyrocumulus clouds from 2013 that either did or did not produce detected lightning. Past research has shown that pyrocumulus cases are most likely to produce lightning when there is a decrease in differential reflectivity (toward 0 dB) and an increase in the correlation coefficient (to >0.8), as measured by polarimetric radar, due to the transition from pure smoke/ash to frozen hydrometeors. All pyrocumulus cases that produced lightning in this study displayed the polarimetric characteristics of rimed ice within their respective clouds. Time series analysis of radar-inferred ash and rimed ice volumes within ash plumes and pyrocumulus clouds showed that NLDN-detected lightning occurred only after the cloud contained significant amounts of precipitation-sized rimed ice. The results suggest that the recently dual-pol-enabled NEXRADs and the more sensitive NLDN network can be used to explore ash plume and pyrocumulus microphysical structure and lightning production.

scholarly journals Estimating parameter values of a socio-hydrological flood model

2018 ◽  
Vol 379 ◽  
pp. 193-198
Author(s):  
Marlies Holkje Barendrecht ◽  
Alberto Viglione ◽  
Heidi Kreibich ◽  
Sergiy Vorogushyn ◽  
Bruno Merz ◽  
...  
Keyword(s):  
Time Series ◽  
Case Studies ◽  
Hydrological Model ◽  
Promising Tool ◽  
Flood Model ◽  
Modelling Studies ◽  
Data Points ◽  
Few Data ◽  
Parameter Values

Abstract. Socio-hydrological modelling studies that have been published so far show that dynamic coupled human-flood models are a promising tool to represent the phenomena and the feedbacks in human-flood systems. So far these models are mostly generic and have not been developed and calibrated to represent specific case studies. We believe that applying and calibrating these type of models to real world case studies can help us to further develop our understanding about the phenomena that occur in these systems. In this paper we propose a method to estimate the parameter values of a socio-hydrological model and we test it by applying it to an artificial case study. We postulate a model that describes the feedbacks between floods, awareness and preparedness. After simulating hypothetical time series with a given combination of parameters, we sample few data points for our variables and try to estimate the parameters given these data points using Bayesian Inference. The results show that, if we are able to collect data for our case study, we would, in theory, be able to estimate the parameter values for our socio-hydrological flood model.

scholarly journals Evaluación de riesgo de cambio, caso de aplicación en empresa importadora

2021 ◽  
Author(s):  
Sindy Viviana Giraldo Arcila ◽  
Juliana López Restrepo
Keyword(s):  
Time Series ◽  
Exchange Rate ◽  
Quantitative Analysis ◽  
Case Studies ◽  
Great Part ◽  
Exchange Rate Risk ◽  
Forecasting Methods ◽  
Black Scholes ◽  
The Impact ◽  
A Company

This applied investigation had as objective to establish a shortterm financial cover to control the impact of loss on profits due to the exchange rate risk on the COP/USD ratio, in a company dedicated to the import and marketing of tires in Colombia. For the above, it was necessary to carry out a quantitative analysis between the options and forward coverage, requiring the use of the Black Scholes technique for the calculation of the premium; Likewise, it was necessary to simulate through different forecasting methods to choose the lowest RMSE error, presented as a result the time series which was used to project the future behavior of the dollar through the Risk Simulator software. Finally, it was evident that a great part of the background for the present investigation is of a qualitative type, some of the existing quantitative origin are not focused on case studies; otherwise, the results obtained allowed to demonstrate that the best coverage is the purchase of the Call in The Money ...

scholarly journals Examining the ACT Model in the Case Study of Taro

2016 ◽  
Vol 11 (4) ◽  
pp. 272
Author(s):  
Steven Hayes
Keyword(s):  
Time Series ◽  
Case Studies ◽  
Clinical Work ◽  
Cultural Factors ◽  
Evidence Based ◽  
Processes Of Change ◽  
Basic Principles ◽  
Target Article ◽  
Evidence Based Model

<p>ACT is a functional contextual form of behavioral and cognitive therapy. It shares commonalities with other contextualistic approaches such as constructivist or narrative therapies, but it differs in its scientific goals. Because of these differences, it is oriented toward manipulable processes linked to basic principles. In this commentary I describe these characteristics and link them to the target article (Muto &amp; Mitamura, 2015). I discuss how a major value of case studies of this kind is the exploration in an intensive way of the links between a model and treatment decisions, processes of change, and outcomes. This recasts somewhat the use of case studies and time series designs in the empirical investigations of ACT, and provides special opportunities for the examination of cultural factors in the application of an evidence-based model. Finally, I note how ACT may help bring together some of the wings of clinical work in Japan.</p>

scholarly journals Time Series Analysis for Assessing and Forecasting of Road Traffic Accidents - Case Studies

2020 ◽  
Vol 19 ◽  
Keyword(s):  
Time Series ◽  
Case Studies ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Public Health Problem ◽  
Road Traffic Accidents ◽  
The Road ◽  
Before And After ◽  
The Uk ◽  
Serious Injuries

Road traffic accident is one of the main causes of injuries and fatalities worldwide, serious injuries and mortality in road collisions being a public health problem. The paper gives a overview of time series modeling and forecasting with application in road traffic injuries monitoring. After presenting of the main models and the methodological issues used in Box-Jenkins approach, the paper discusses two case studies, using a multiplicative SARIMA model and an intervention model, for a time series representing the number of mortal traffic accidents in USA, and the road traffic accidents with death and serious injuries in the UK, before and after the imposition of the Arabian embargo in November 1973.

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