Results 101 to 110 of about 6,660,147 (290)
Sustainable Development, EarlyView.ABSTRACT This study examines how home‐ and host‐country institutions jointly shape the impact of foreign direct investment (FDI) on firms' climate action commitments (CAC) in emerging markets. Drawing on New Institutional Economics and Varieties of Capitalism, we conceptualize FDI as a mechanism of institutional transmission through which multinational
Jose Pla‐Barber, David Tobón‐Orozco
wiley +1 more source
ARIMA Model Selection and Prediction Intervals
AxiomsInference after model selection is a very important problem. Model selection algorithms for ARIMA time series, with criteria such as AIC and BIC, tend to select an inconsistent model with positive probability, making data-splitting inference for testing and confidence intervals unreliable. One technique was fairly reliable for sample sizes greater than
Welagedara Arachchilage Dhanushka M. Welagedara +2 more
openaire +1 more source
IDENTIFIKASI MODEL FLUKTUASI INDEKS K HARIAN MENGGUNAKAN MODEL ARIMA (2.0.1)
, 2005 The geomagnetic level called geomagnetic index. Based on the latitude, geomagnetic index for high to intermediate latitude is Kp index and for equator area is Dst index. For a certain location it is called local geomagnetic index, K index.
Habirun
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Sustainable Development, EarlyView.ABSTRACT In recent years, transition to renewable energy has emerged as a vital strategy for achieving sustainable development and reducing environmental degradation. Only when backed by a solid institutional and macroeconomic context can economic growth serve as a stimulus for the development of renewable energy.
Azad Erdem +3 more
wiley +1 more source
Missing observations and additive outliers in time series models. [PDF]
The paper deals with estimation of missing observations in possible nonstationary ARIMA models. First, the model is assumed known, and the structure of the interpolation filter is analyzed.
Maravall, Agustín, Peña, Daniel
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Sustainable Development, EarlyView.ABSTRACT Climate mitigation policies in the Brazilian Legal Amazon have largely focused on aggregate or net emissions, providing limited evidence on how gross agricultural emissions reveal the intensity of productive emission sources independently of carbon removals.
Jorge Eduardo Macedo Simões +4 more
wiley +1 more source
Automatic time series forecasting: the forecast package for R. [PDF]
Automatic forecasts of large numbers of univariate time series are often needed in business and other contexts. We describe two automatic forecasting algorithms that have been implemented in the forecast package for R.
Rob J. Hyndman, Yeasmin Khandakar
core +2 more sources
Network Latency Estimation for Telesurgery Using Deep Reinforcement Learning
SmartBot, EarlyView.Overview of the proposed two‐stage deep reinforcement learning framework for network latency prediction in telesurgery. The pipeline includes data collection from simulated catheter navigation sessions (Philippines–Botswana), feature engineering, DQN‐based direction prediction (85.8% accuracy), direction‐to‐value transformation, and value forecasting ...
Bakang Kgopolo +2 more
wiley +1 more source
Carbon Speciation and Solubility in Silicate Melts
Geophysical Monograph Series, Page 179-194., 2020 This book is Open Access. A digital copy can be downloaded for free from Wiley Online Library.
Explores the behavior of carbon in minerals, melts, and fluids under extreme conditions
Carbon trapped in diamonds and carbonate-bearing rocks in subduction zones are examples of the continuing exchange of substantial carbon ...
Natalia Solomatova +2 more
wiley +1 more source
Forecasting Inflation in Developing Nations: The Case of Pakistan [PDF]
This study attempts to outline the practical steps which need to be undertaken to use autoregressive integrated moving average (ARIMA) time series models for forecasting Pakistan’s inflation. A framework for ARIMA forecasting is drawn up. On the basis of
Feridun, Mete
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