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Journals / İstatistik Araştırma Dergisi / 2026 / Cilt: 8 Sayı: 2 Özel Sayı

Modeling İzmir Temperature Data With Spline Regression

İzmir İli Sıcaklık Verilerinin Regresyon Eğrileri ile Modellenmesi

Neslihan Demirel(DOKUZ EYLÜL ÜNİVERSİTESİ, FEN FAKÜLTESİ, İSTATİSTİK BÖLÜMÜ)
Pages
68–75
Publication Date
2011-10-17
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Spline regression method is applied for analyzing each of the data sets.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Spline regression is a type of non-parametric regression analysis which is frequently applied in economy, finance, medicine and political sciences.
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Key Findings & Data:In this study, 34 years of temperature data taken from Turkish State Meteorological Service for Izmir is examined under the condition that the locations of knot points are known and unknown.
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Conclusion & Impact:Spline regression method is applied for analyzing each of the data sets.
🔬Design:Konferans Bildirisi
📍Scope:Comprehensive Sample
⚙️Variables:Düğüm Noktası · Sıcaklık Verisi · Regresyon Eğrileri Modelleri

Abstract

Spline regression is a type of non-parametric regression analysis which is frequently applied in economy, finance, medicine and political sciences. In this study, 34 years of temperature data taken from Turkish State Meteorological Service for Izmir is examined under the condition that the locations of knot points are known and unknown. Spline regression method is applied for analyzing each of the data sets.

Özet

Regresyon eğrileri parametrik olmayan bir regresyon analizi türüdür. Regresyon çözümlemesine farklı bir yaklaşım getiren bu yöntem, ekonomi, finans, tıp ve politik bilimlerde sıkça kullanılmaktadır. Bu çalışmada; Devlet Meteoroloji İşleri Genel Müdürlüğünden alınan İzmir iline ait 34 yıllık sıcaklık verileri, düğüm noktalarının konumlarının bilinmesi ve bilinmemesi durumları için ayrı ayrı incelenmiştir. Her bir veri kümesine regresyon eğrileri uygulanarak modellenmiştir.

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Cite This Article

Demirel, N. (2011). Modeling İzmir Temperature Data With Spline Regression. İstatistik Araştırma Dergisi, Cilt: 8 Sayı: 2 Özel Sayı, 68–75. https://ajindex.com/articles/1617853

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References (8)

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