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You searched for subject:(quantitative forecasting methods). Showing records 1 – 9 of 9 total matches.

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1. Pungartnik, Tadej. Napovedovanje proizvodnega programa.

Degree: 2015, Univerza v Mariboru

V magistrski nalogi je predstavljena problematika napovedovanja. V teoretičnem delu je najprej prikazan proces in pomen napovedovanja, ter dejavniki, ki vplivajo na napovedovanje. Sledi podroben… (more)

Subjects/Keywords: napovedovanje; časovna vrsta; kvalitativne metode napovedovanja; kvantitativne metode napovedovanja; natančnost napovedovanja; forecasting; time series; qualitative forecasting methods; quantitative forecasting methods; forecasting accuracy; info:eu-repo/classification/udc/[005.521:519.24]:658.5(043.2)

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APA (6th Edition):

Pungartnik, T. (2015). Napovedovanje proizvodnega programa. (Masters Thesis). Univerza v Mariboru. Retrieved from https://dk.um.si/IzpisGradiva.php?id=47976 ; https://dk.um.si/Dokument.php?id=71632&dn= ; https://plus.si.cobiss.net/opac7/bib/18801174?lang=sl

Chicago Manual of Style (16th Edition):

Pungartnik, Tadej. “Napovedovanje proizvodnega programa.” 2015. Masters Thesis, Univerza v Mariboru. Accessed August 18, 2019. https://dk.um.si/IzpisGradiva.php?id=47976 ; https://dk.um.si/Dokument.php?id=71632&dn= ; https://plus.si.cobiss.net/opac7/bib/18801174?lang=sl.

MLA Handbook (7th Edition):

Pungartnik, Tadej. “Napovedovanje proizvodnega programa.” 2015. Web. 18 Aug 2019.

Vancouver:

Pungartnik T. Napovedovanje proizvodnega programa. [Internet] [Masters thesis]. Univerza v Mariboru; 2015. [cited 2019 Aug 18]. Available from: https://dk.um.si/IzpisGradiva.php?id=47976 ; https://dk.um.si/Dokument.php?id=71632&dn= ; https://plus.si.cobiss.net/opac7/bib/18801174?lang=sl.

Council of Science Editors:

Pungartnik T. Napovedovanje proizvodnega programa. [Masters Thesis]. Univerza v Mariboru; 2015. Available from: https://dk.um.si/IzpisGradiva.php?id=47976 ; https://dk.um.si/Dokument.php?id=71632&dn= ; https://plus.si.cobiss.net/opac7/bib/18801174?lang=sl

2. Bokan, Benjamin. Napovedovanje proizvodnega programa v podjetju Arcont d.d.

Degree: 2017, Univerza v Mariboru

Magistrsko delo se osredotoča na problematiko napovedovanja proizvodnega programa v podjetju Arcont d.d.

v glavnem je razdeljeno na teoretični in praktični del. Teoretični del zajema… (more)

Subjects/Keywords: napovedovanje; natančnost napovedovanja; kvalitativne metode napovedovanja; kvantitativne metode napovedovanja; forecasting; forecasting accuracy; qualitative forecasting methods; quantitative forecasting methods; info:eu-repo/classification/udc/005.521:658.51(043.2)

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APA (6th Edition):

Bokan, B. (2017). Napovedovanje proizvodnega programa v podjetju Arcont d.d. (Masters Thesis). Univerza v Mariboru. Retrieved from https://dk.um.si/IzpisGradiva.php?id=66871 ; https://dk.um.si/Dokument.php?id=117192&dn= ; https://plus.si.cobiss.net/opac7/bib/21180182?lang=sl

Chicago Manual of Style (16th Edition):

Bokan, Benjamin. “Napovedovanje proizvodnega programa v podjetju Arcont d.d.” 2017. Masters Thesis, Univerza v Mariboru. Accessed August 18, 2019. https://dk.um.si/IzpisGradiva.php?id=66871 ; https://dk.um.si/Dokument.php?id=117192&dn= ; https://plus.si.cobiss.net/opac7/bib/21180182?lang=sl.

MLA Handbook (7th Edition):

Bokan, Benjamin. “Napovedovanje proizvodnega programa v podjetju Arcont d.d.” 2017. Web. 18 Aug 2019.

Vancouver:

Bokan B. Napovedovanje proizvodnega programa v podjetju Arcont d.d. [Internet] [Masters thesis]. Univerza v Mariboru; 2017. [cited 2019 Aug 18]. Available from: https://dk.um.si/IzpisGradiva.php?id=66871 ; https://dk.um.si/Dokument.php?id=117192&dn= ; https://plus.si.cobiss.net/opac7/bib/21180182?lang=sl.

Council of Science Editors:

Bokan B. Napovedovanje proizvodnega programa v podjetju Arcont d.d. [Masters Thesis]. Univerza v Mariboru; 2017. Available from: https://dk.um.si/IzpisGradiva.php?id=66871 ; https://dk.um.si/Dokument.php?id=117192&dn= ; https://plus.si.cobiss.net/opac7/bib/21180182?lang=sl

3. Kornprobst, Antoine. Financial crisis forecasts and applications to systematic trading strategies : Indicateurs de crises financières et applications aux stratégies de trading algorithmique.

Degree: Docteur es, Mathématiques appliquées, 2017, Paris 1

Cette thèse, constituée de trois papiers de recherche, est organisée autour de la construction d’indicateurs de crises financières dont les signaux sont ensuite utilisés pour… (more)

Subjects/Keywords: Crises financières; Économétrie; Indicateurs; Quantitative finance; Econometrics; Simulation methods; Forecasting; Large data sets; Financial crises; Random matrix theory; 519

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APA (6th Edition):

Kornprobst, A. (2017). Financial crisis forecasts and applications to systematic trading strategies : Indicateurs de crises financières et applications aux stratégies de trading algorithmique. (Doctoral Dissertation). Paris 1. Retrieved from http://www.theses.fr/2017PA01E067

Chicago Manual of Style (16th Edition):

Kornprobst, Antoine. “Financial crisis forecasts and applications to systematic trading strategies : Indicateurs de crises financières et applications aux stratégies de trading algorithmique.” 2017. Doctoral Dissertation, Paris 1. Accessed August 18, 2019. http://www.theses.fr/2017PA01E067.

MLA Handbook (7th Edition):

Kornprobst, Antoine. “Financial crisis forecasts and applications to systematic trading strategies : Indicateurs de crises financières et applications aux stratégies de trading algorithmique.” 2017. Web. 18 Aug 2019.

Vancouver:

Kornprobst A. Financial crisis forecasts and applications to systematic trading strategies : Indicateurs de crises financières et applications aux stratégies de trading algorithmique. [Internet] [Doctoral dissertation]. Paris 1; 2017. [cited 2019 Aug 18]. Available from: http://www.theses.fr/2017PA01E067.

Council of Science Editors:

Kornprobst A. Financial crisis forecasts and applications to systematic trading strategies : Indicateurs de crises financières et applications aux stratégies de trading algorithmique. [Doctoral Dissertation]. Paris 1; 2017. Available from: http://www.theses.fr/2017PA01E067


University of Tennessee – Knoxville

4. Meng, Fanning. Economic Forecasting with Many Predictors.

Degree: 2017, University of Tennessee – Knoxville

 The dissertation is focused on the analysis of economic forecasting with a large number of predictors. The first chapter develops a novel forecasting method that… (more)

Subjects/Keywords: Forecasting; Quantile Regression; MIDAS; LASSO; Feature-selection; Econometrics; International Economics; Macroeconomics; Management Information Systems; Management Sciences and Quantitative Methods

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APA (6th Edition):

Meng, F. (2017). Economic Forecasting with Many Predictors. (Doctoral Dissertation). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_graddiss/4483

Chicago Manual of Style (16th Edition):

Meng, Fanning. “Economic Forecasting with Many Predictors.” 2017. Doctoral Dissertation, University of Tennessee – Knoxville. Accessed August 18, 2019. https://trace.tennessee.edu/utk_graddiss/4483.

MLA Handbook (7th Edition):

Meng, Fanning. “Economic Forecasting with Many Predictors.” 2017. Web. 18 Aug 2019.

Vancouver:

Meng F. Economic Forecasting with Many Predictors. [Internet] [Doctoral dissertation]. University of Tennessee – Knoxville; 2017. [cited 2019 Aug 18]. Available from: https://trace.tennessee.edu/utk_graddiss/4483.

Council of Science Editors:

Meng F. Economic Forecasting with Many Predictors. [Doctoral Dissertation]. University of Tennessee – Knoxville; 2017. Available from: https://trace.tennessee.edu/utk_graddiss/4483


University of Pennsylvania

5. Ham, Wendy. Computational Models of Information Processing.

Degree: 2014, University of Pennsylvania

 The necessity and desire to understand the nature of information permeates virtually all aspects of scientific endeavors in both natural and social systems. This is… (more)

Subjects/Keywords: Computational modeling; Forecasting; Information processing; Knowledge acquisition; Network; Simulation; Business Administration, Management, and Operations; Management Sciences and Quantitative Methods

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APA (6th Edition):

Ham, W. (2014). Computational Models of Information Processing. (Thesis). University of Pennsylvania. Retrieved from https://repository.upenn.edu/edissertations/1304

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ham, Wendy. “Computational Models of Information Processing.” 2014. Thesis, University of Pennsylvania. Accessed August 18, 2019. https://repository.upenn.edu/edissertations/1304.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ham, Wendy. “Computational Models of Information Processing.” 2014. Web. 18 Aug 2019.

Vancouver:

Ham W. Computational Models of Information Processing. [Internet] [Thesis]. University of Pennsylvania; 2014. [cited 2019 Aug 18]. Available from: https://repository.upenn.edu/edissertations/1304.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ham W. Computational Models of Information Processing. [Thesis]. University of Pennsylvania; 2014. Available from: https://repository.upenn.edu/edissertations/1304

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Arkansas

6. Jin, Yao. Data Science in Supply Chain Management: Data-Related Influences on Demand Planning.

Degree: PhD, 2013, University of Arkansas

  Data-driven decisions have become an important aspect of supply chain management. Demand planners are tasked with analyzing volumes of data that are being collected… (more)

Subjects/Keywords: Social sciences; Applied sciences; Collaboration and integration; Data science; Demand planning; Forecasting; Information sharing; Supply chain management; Management Information Systems; Management Sciences and Quantitative Methods; Operations and Supply Chain Management

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Jin, Y. (2013). Data Science in Supply Chain Management: Data-Related Influences on Demand Planning. (Doctoral Dissertation). University of Arkansas. Retrieved from https://scholarworks.uark.edu/etd/898

Chicago Manual of Style (16th Edition):

Jin, Yao. “Data Science in Supply Chain Management: Data-Related Influences on Demand Planning.” 2013. Doctoral Dissertation, University of Arkansas. Accessed August 18, 2019. https://scholarworks.uark.edu/etd/898.

MLA Handbook (7th Edition):

Jin, Yao. “Data Science in Supply Chain Management: Data-Related Influences on Demand Planning.” 2013. Web. 18 Aug 2019.

Vancouver:

Jin Y. Data Science in Supply Chain Management: Data-Related Influences on Demand Planning. [Internet] [Doctoral dissertation]. University of Arkansas; 2013. [cited 2019 Aug 18]. Available from: https://scholarworks.uark.edu/etd/898.

Council of Science Editors:

Jin Y. Data Science in Supply Chain Management: Data-Related Influences on Demand Planning. [Doctoral Dissertation]. University of Arkansas; 2013. Available from: https://scholarworks.uark.edu/etd/898


University of Pennsylvania

7. Dietvorst, Berkeley Jay. Algorithm Aversion.

Degree: 2016, University of Pennsylvania

 Research shows that evidence-based algorithms more accurately predict the future than do human forecasters. Yet when forecasters are deciding whether to use a human forecaster… (more)

Subjects/Keywords: Confidence; Decision aids; Decision making; Forecasting; Heuristics and biases; Prediction; Advertising and Promotion Management; Business Administration, Management, and Operations; Management Sciences and Quantitative Methods; Marketing; Psychology

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APA (6th Edition):

Dietvorst, B. J. (2016). Algorithm Aversion. (Thesis). University of Pennsylvania. Retrieved from https://repository.upenn.edu/edissertations/1686

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Dietvorst, Berkeley Jay. “Algorithm Aversion.” 2016. Thesis, University of Pennsylvania. Accessed August 18, 2019. https://repository.upenn.edu/edissertations/1686.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Dietvorst, Berkeley Jay. “Algorithm Aversion.” 2016. Web. 18 Aug 2019.

Vancouver:

Dietvorst BJ. Algorithm Aversion. [Internet] [Thesis]. University of Pennsylvania; 2016. [cited 2019 Aug 18]. Available from: https://repository.upenn.edu/edissertations/1686.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Dietvorst BJ. Algorithm Aversion. [Thesis]. University of Pennsylvania; 2016. Available from: https://repository.upenn.edu/edissertations/1686

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

8. Γεόμελος, Νικόλαος. Εφαρμοσμένες τεχνικές οικονομετρικής προβλεψιμότητας στις ναυτιλιακές αγορές.

Degree: 2012, University of the Aegean; Πανεπιστήμιο Αιγαίου

 Econometrics constitutes a modern science, which has as aim to study, analyze and to interpret complicated economical phenomena, through sophisticated models and applications. Shipping, as… (more)

Subjects/Keywords: Εφαρμοσμένη οικονομετρία; Οικονομετρική ανάλυση; Ποσοτικές μέθοδοι; Ναυτιλιακή οικονομική; Ναυτιλιακές αγορές; Ex-post προβλέψεις; Ex-ante προβλέψεις; Applied econometrics; Econometric analysis; Quantitative methods; Shipping economy – maritime economics; Shipping markets; Ex-post forecasting; Ex-ante forecasting

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APA (6th Edition):

Γεόμελος, . . (2012). Εφαρμοσμένες τεχνικές οικονομετρικής προβλεψιμότητας στις ναυτιλιακές αγορές. (Thesis). University of the Aegean; Πανεπιστήμιο Αιγαίου. Retrieved from http://hdl.handle.net/10442/hedi/27656

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Γεόμελος, Νικόλαος. “Εφαρμοσμένες τεχνικές οικονομετρικής προβλεψιμότητας στις ναυτιλιακές αγορές.” 2012. Thesis, University of the Aegean; Πανεπιστήμιο Αιγαίου. Accessed August 18, 2019. http://hdl.handle.net/10442/hedi/27656.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Γεόμελος, Νικόλαος. “Εφαρμοσμένες τεχνικές οικονομετρικής προβλεψιμότητας στις ναυτιλιακές αγορές.” 2012. Web. 18 Aug 2019.

Vancouver:

Γεόμελος . Εφαρμοσμένες τεχνικές οικονομετρικής προβλεψιμότητας στις ναυτιλιακές αγορές. [Internet] [Thesis]. University of the Aegean; Πανεπιστήμιο Αιγαίου; 2012. [cited 2019 Aug 18]. Available from: http://hdl.handle.net/10442/hedi/27656.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Γεόμελος . Εφαρμοσμένες τεχνικές οικονομετρικής προβλεψιμότητας στις ναυτιλιακές αγορές. [Thesis]. University of the Aegean; Πανεπιστήμιο Αιγαίου; 2012. Available from: http://hdl.handle.net/10442/hedi/27656

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Portland State University

9. Heger, Roland Helmut. Value Measurement for New Product Category: a Conjoint Approach to Eliciting Value Structure.

Degree: PhD, Systems Science: Business Administration, 1996, Portland State University

  Ability to measure value from the customer's point of view is central to the determination of market offerings: Customers will only buy the equivalent… (more)

Subjects/Keywords: New products  – Marketing  – Forecasting; New products  – Marketing  – Mathematical models; Conjoint analysis (Marketing); Management Sciences and Quantitative Methods; Marketing

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APA (6th Edition):

Heger, R. H. (1996). Value Measurement for New Product Category: a Conjoint Approach to Eliciting Value Structure. (Doctoral Dissertation). Portland State University. Retrieved from https://pdxscholar.library.pdx.edu/open_access_etds/1305

Chicago Manual of Style (16th Edition):

Heger, Roland Helmut. “Value Measurement for New Product Category: a Conjoint Approach to Eliciting Value Structure.” 1996. Doctoral Dissertation, Portland State University. Accessed August 18, 2019. https://pdxscholar.library.pdx.edu/open_access_etds/1305.

MLA Handbook (7th Edition):

Heger, Roland Helmut. “Value Measurement for New Product Category: a Conjoint Approach to Eliciting Value Structure.” 1996. Web. 18 Aug 2019.

Vancouver:

Heger RH. Value Measurement for New Product Category: a Conjoint Approach to Eliciting Value Structure. [Internet] [Doctoral dissertation]. Portland State University; 1996. [cited 2019 Aug 18]. Available from: https://pdxscholar.library.pdx.edu/open_access_etds/1305.

Council of Science Editors:

Heger RH. Value Measurement for New Product Category: a Conjoint Approach to Eliciting Value Structure. [Doctoral Dissertation]. Portland State University; 1996. Available from: https://pdxscholar.library.pdx.edu/open_access_etds/1305

.