trend models

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1. 1▶02417 Lecture 1 part B - Fall 201802417 Time Series AnalysisNotes
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2. 2▶02417 Lecture 1 part A - Fall 201802417 Time Series AnalysisNotes
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3. 3▶02417 Lecture 4 part C: Local trend model02417 Time Series AnalysisNotes
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4. 4▶02417 Lecture 4 part A: Exponential smoothing02417 Time Series AnalysisNotes
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5. 5▶02417 Lecture 4 part B: Choosing lambda in exponential smoothing02417 Time Series AnalysisNotes
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6. 6▶02417 Lecture 4 part D: Variance in local trend models02417 Time Series AnalysisNotes
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7. 7▶02417 Lecture 4 part E: Variance in local trend models - simulation example02417 Time Series AnalysisNotes
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8. 8▶02417 Lecture 2 part A: Ordinary least squares in linear model02417 Time Series AnalysisNotes
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9. 9▶02417 Lecture 2 part B: Ordinary least squares - continued02417 Time Series AnalysisNotes
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10. 10▶02417 Lecture 2 part C: Weighted least squares02417 Time Series AnalysisNotes
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11. 11▶02417 Lecture 2 part D: Predicting in linear models02417 Time Series AnalysisNotes
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12. 12▶02417 Lecture 3 part A: Global trend models02417 Time Series AnalysisNotes
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13. 13▶02417 Lecture 3 part B: Estimating in global trend models02417 Time Series AnalysisNotes
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14. 14▶02417 Lecture 3 part C: Global trend model - example02417 Time Series AnalysisNotes
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15. 15▶02417 Lecture 3 part D: R example on regression02417 Time Series AnalysisNotes
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