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          • accuracy
          • adjusted_r2
          • assumptions of linear discriminant analysis
          • autocorrelation
          • autoregression
          • bias
          • bias-variance tradeoff
          • boosting
          • bootstrap
          • causality test
          • classification
          • confusion matrix
          • cross valiation
          • decision tree
          • differencing
          • f1-score
          • Gini coefficient
          • Homoscedasticity
          • k-fold cross valiation
          • kernel trick
          • linear discriminant analysis
          • logistic regression
          • logloss
          • mean absolute error
          • mean squared error
          • model complexity
          • moving average
          • naive Bayes
          • natural language processing
          • partial autocorrelation
          • precision
          • r2
          • recall
          • regression
          • residual sum of squares
          • root mean squared error
          • stationary
          • stationary test
          • support vector classifiers
          • support vectors
          • text tokenization
          • total sum of squares
          • weak models
            • 6. Time Series with Pandas
            • 6.1. DateTime Index
            • 6.2. DateTime Index Part Two
            • 6.3. Time Resampling
            • 6.4. Time Shifting
            • 6.5. Rolling and Expanding
            • 6.6. Visualizing Time Series Data
            • 6.7. Visualizing Time Series Data - Part Two
            • 7. Time Series Analysis with Statsmodels
            • 7.1. Introduction to Statsmodels Library
            • 7.2. ETS Decomposition
            • 7.3. EWMA Theory
            • 7.4. EWMA Exponential Weighted Moving Average
            • 7.5. Holt-Winters Method Theory
            • 7.6. Holt-Winters Method Code - Part 1
            • 7.7. Holt-Winters Method Code - Part 2
            • 8. General Forecasting
            • 8.1 Introduction to Forecasting Models Part 1
            • 8.2 Evaluating Forecast Predictions
            • 8.3 Introduction to Forecasting Models Part 2
            • 8.4 ACF and PACF Theory
            • 8.5 ACF and PACF Code Along
            • 8.6 ARIMA Overview
            • 8.7 Autoregression - AR - Overview
            • 8.8 Autoregression - AR with Statmodels
            • 8.9 Descriptive Statistics and Tests - Part 1
            • 8.10 Descriptive Statistics and Tests - Part 2
            • 8.11 Descriptive Statistics and Tests - Part 3
            • 8.12 Arima Theory Overview
            • 8.13 Choosing ARIMA Orders - Part 1
            • 8.13 Choosing ARIMA Orders - Part 2
            • 8.14 ARMA and ARIMA - AutoRegressive Integrated Moving Average - Part 1
            • 8.14 ARMA and ARIMA - AutoRegressive Integrated Moving Average - Part 2
            • 8.15. SARIMA - Seasonal Autoregressive Integrated Moving Average
            • 8.16 SARIMAX - Seasonal Autoregressive Integrated Moving Average Exogenous - Part 1
            • 8.17 SARIMAX - Seasonal Autoregressive Integrated Moving Average Exogenous - Part 2
        • $\chi^2$ Distribution
        • A New Way to Predict Probability Distributions by Harrison Hoffman Feb, 2023 Towards Data Science
        • Chi-Square and Standard Normal Theorem
        • Confidence Level
        • Construction of Manifold in R2
        • Correlation — When Pearson’s r Is Not Enough by Farzad Mahmoodinobar Feb, 2023 Towards Data Science
        • Decision Rule
        • Example - Differentiation of a Differential Form
        • Gamma, Exponential and Chi-Squared Distributions
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        • Log-Normal Distribution
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        • Poisson as the Limit of Binomial Distribution
        • Properties of Differentiation
        • README
        • Recall Hypothesis Test
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        • Type-II Error Rate
        • Understanding Noisy Data and Uncertainty in Machine Learning by Harrison Hoffman Jan, 2023 Towards Data Science
        • 17 Statistical Hypothesis Tests in Python (Cheat Sheet)
        • A Gentle Introduction to Statistical Hypothesis Testing
        • README
          • Bernoulli Distribution
          • Beta Distribution
          • Binomial Distribution
          • Exponential Distribution
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          • Gaussian Distribution
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        • Akaike Information Criterion
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        • Borel Sigma Algebra
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        • Chi-Squared Test
        • Closed and bounded sets are compact
        • Closed Set
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        • Closed Subsets are Compact
        • Closure of a Set
        • Closure of a Set is Closed
        • Compact Set
        • Compact Subsets of a Hausdorff Space are Closed
        • Compact Topological Space
        • Compatability of Coordinates
        • Complete Metric Space
        • Conditional Probability
        • Connected Topological Space
        • Continous Differentiability
        • Continuity in terms of Preimage
        • Continuous Function
        • Contracting Mapping Theorem
        • Convergence of a Sequence in terms of a Metric
        • Convergence of a Sequence in terms of Open Sets
        • Convergent and Cauchy Sequences
        • Coordinate Neighborhood
        • Corollary Tangent Vectors are Derivations
        • Correlation of Random Variables
        • Cotangent Space
        • Countably Additive Function
        • Covariance of Random Variables
        • Covariance, Correlation and Independence
        • Covector Field
        • Cover
        • Curve
        • D’Agostino’s $K^2$ Test
        • Density
        • Derivation
        • Diffeomorphism
        • Differentiability and Partial Derivatives
        • Differentiable
        • Differentiable Manifold
        • Differential Forms
        • Differentiation Of Differental Forms
        • Directional Derivative
        • Dual Space
        • Entropy
        • Euclidean Product of Differentiable Manifolds
        • Euclidean Space
        • Euclidean Tangent Space
        • Existence of Isometric Spaces
        • Expected Value of a Random Variable
        • First Variation
        • Friedman Test
        • Functional
        • Functions and Mappings
        • Gaussian is the Limit of Binomial
        • Gaussian is the Limit of Poisson
        • Hausdorff Space
        • Hausdorff Topological Space
        • Hilbert Space
        • Homeomorphism
        • Image of an Open Set Under Continuous Function
        • Induced Topology of a Metric
        • Inner Product
        • Interior of a Set
        • Interior Point and Interior of a Set
        • Inverse Function Theorem
        • Isometric Spaces
        • Jacobian Matrix
        • Kendall’s Rank Correlation
        • Kruskal-Wallis H
        • Kwiatkowski-Phillips-Schmidt-Shin
        • Lebesgue Integral
        • Lebesgue Measure
        • Likelihood Function
        • Limit of a Sequence
        • Local Criterion for Openness
        • Local Minimum
        • Locally Euclidean
        • Lp Norm
        • Mann-Whitney U Test
        • Markov Chain Monte Carlo
        • Measurable Function
        • Measure
        • Measure Space
        • Metric
        • Metric Neighborhood
        • Metric Open Set
        • Metric Set Closure
        • Metric Space
        • Metric Spaces are Hausdorff
        • Metrical Continuous Function
        • Metrizable Topological Space
        • Moment Generating Function
        • Monte Carlo
        • N-form
        • Negative Binomial Distribution
        • Neighborhood
        • Norm
        • Open Ball
        • Open Balls and Open Sets
        • Open Balls Are Open Sets
        • Open Set
        • Open Set and Interior
        • Orientation
        • Paired Student’s T-test
        • Partial Derivative
        • Partition of Unity
        • Pearson’s Correlation Coefficient
        • Pointwise Continuity
        • Poisson Distribution
        • Preimage
        • Probability Density Function
        • Probability Distribution
        • Probability Mass Function
        • Probability Measure
        • Random Variable
        • Rank of a Matrix
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        • Rank Theorem
        • README
        • Relationship between metric and norm
        • Repeated Measures ANOVA Test
        • Sequence
        • Sequence lemma
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        • Set Closure
        • Shapiro-Wilk
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        • Spearman’s Rank Correlation
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        • Student’s T-test
        • Tangent Space
        • Tangent Vectors as Derivations
        • The Relationship Between Topological and Measurable Spaces
        • Topological Continuous Function
        • Topological Cover
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        • Topological Space
        • Topological Space Induced by the Metric Space
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        • Uniqueness of Coordinates
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        • Vector Field
        • Vector Fields as Derivations
        • Vector Space
        • Wilcoxon Signed-Rank Test
        • [object Object]
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        • A comprehensive introduction do differential geometry
        • A geometric approach to differential forms
        • A Short Introduction to Metric Spaces
        • An introduction to differentiable manifolds and riemannian geometry
        • An introduction to machine learning
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        • Theories of Integration: the Integrals of Riemann, Lebesgue, Henstock-Kurzweil, and McShane, S. in Real Analysis
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    7. Time Series Analysis with Statsmodels

    7. Time Series Analysis with Statsmodels

    Apr 23, 20241 min read

    Main library to do time series analysis

    7.1. Introduction to Statsmodels Library 7.2. ETS Decomposition 7.3. EWMA Theory 7.4. EWMA Exponential Weighted Moving Average 7.5. Holt-Winters Method Theory 7.6. Holt-Winters Method Code - Part 1 7.7. Holt-Winters Method Code - Part 2

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