Sökning: "Vector Auto-regressive model"

Visar resultat 1 - 5 av 8 uppsatser innehållade orden Vector Auto-regressive model.

1. 1. Does industry survey data improve GDP forecasting?

   Kandidat-uppsats, Göteborgs universitet/Företagsekonomiska institutionen

   Författare :Oscar Andersson; Ludvig Fornstedt; [2024-03-06]
   Nyckelord :Bayesian; BVAR; Forecasting; GDP; survey data;

   Sammanfattning : This study assesses the integration of industry survey data into Bayesian Vector Auto Regressive (BVAR) models for GDP forecasting in Sweden. Analyzing a combination of macro economic indicators, CPI and unemployment rates, with survey data from NIER, it explores the effects of different variable combinations on the forecasting ability of different models. LÄS MER

3. 2. Causal Discovery for Time Series : Based on Continuous Optimization

   Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Författare :Ali Nouri; [2023]
   Nyckelord :;

   Sammanfattning : Causal discovery is an important field of study that seeks to understand the underlying relationships between variables in a system. The goal of causal discovery is to discover the causal relationships from observational data and determine the direction of influence between variables. LÄS MER

4. 3. Data-Driven Traffic Forecasting for Completed Vehicle Simulation: : A Case Study with Volvo Test Trucks

   Magister-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Författare :Samaneh Shahrokhi; [2023]
   Nyckelord :supervised machine learning; traffic forecasting; vehicle presence prediction; binary classification; ensemble learning; feature engineering; hyperparameter tuning; data-driven analysis;

   Sammanfattning : This thesis offers a thorough investigation into the application of machine learning algorithms for predicting the presence of vehicles in a traffic setting. The research primarily focuses on enhancing vehicle simulation by employing data-driven traffic prediction methods. The study approaches the problem as a binary classification task. LÄS MER

5. 4. Machine LearningMethods for Forecasting Product Demand: A case study with telecommunications software

   D-uppsats, Handelshögskolan i Stockholm/Institutionen för nationalekonomi

   Författare :Meghan Byars; [2021]
   Nyckelord :demand forecasting; machine learning; time series forecasting; random forest; SARIMA;

   Sammanfattning : There is a lack of evidence pointing to an optimal method for demand forecasting. This paper joins the collection of studies that forecast demand using a combination of machine learning methods. LÄS MER

7. 5. Short-Term Heat Load Forecasting in District Heating Systems : A Comparative Study of Various Forecasting Methods

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Zacharias Poutiainen; [2019]
   Nyckelord :;

   Sammanfattning : Short term heat load forecasts are vital for optimal production planning and commitment of generation units. The generation utility also bares a balance responsibility toward the electricity market as a result of CHP generation. Sub-optimal load forecasts can lead to high costs relating to unit commitment, fuel usage and balancing costs. LÄS MER