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Regresión Lineal Simple + Modelos Machine Learning en Series temporales

Buenos días,

El proyecto tiene 3 secciones:

I. Estimación de modelos OLS

El objetivo del proyecto es construir una función para evaluar distintas estructuras de modelos de regresión lineal. tener en cuenta lo siguiente:

1. La función debe recorrer desde el rezago 2 de la variable hasta el adelanto 4 (o lead 4).

2. Cumplir con el sentido de signo que se le imponga aquellos que no cumplan deben ser excluidos de los resultados finales, además de los que no tengan un pvalue menor al 10% (b1>0 y pvalue(b1)<10%).

3. En el caso que una variable y su transformación ingresen (b1*X+b2*X_lag1) se debe cumplir que la suma de ambos coeficientes cumplan con el signo esperado (b1+b2>0, por ejemplo).

4. Si ingresan más de dos transformación se debe asegurar que haya continuidad por lo que se esperaría algo como:b1*X+b2*X_lag1+b3*X_lead1 y no b1*X+b2*X_lag1+b3*X_lead2. Este segundo modelo se excluye.

5. Se considerará más de una variable independiente (X1,X2) debe considerarse como un producto cartesiano dado que ingresarán sus transformaciones.

6. En la variable independientes debe ingresar el rezago de la variable dependiente.

Hay algunas cosas adicionales que se comentarán directamente.

II. Elaboración de una función para evaluar test de raíz unitaria ADF, PP, etc, que se encuentran el paquete statmodels de Python o esta guía ([login to view URL]).

III. Estimación y pronóstico fuera de la muestra (outsample) de modelos de machine y deep learning, con un componente autoregresivo. Muchos de los modelos están acá ([login to view URL])

Por favor, solo realizar propuestas personas de habla hispana o español. No otros idiomas por favor!

Kemahiran: Python, Machine Learning (ML), Econometrics, Deep Learning, Linear Regression

Tentang Klien:
( 6 ulasan ) Lima, Peru

ID Projek: #34395970

19 pekerja bebas membida secara purata $193 untuk pekerjaan ini

(77 Ulasan)
7.1
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