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README.Rmd

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8. `data_transform` is a wrapper for standardizing `data.frame` to make the values comparable for estimation and/or visualization.
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8. `estimate_plot` is a function for plotting estimated coefficients of a model in their order of significance.
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8. `corplot` is for plotting the correlation matrix.
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## Things the package can do
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The package is capable of
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* Inverse scaled logit for constrained forecast
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* Linear regression and transformations which consists of
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* Linear regression and functional forms which consists of
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+ Linear model
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+ Linear model with interactions
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+ Semilog model
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+ Growth model
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+ Double Log model
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+ Mixed-power model
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+ Translog model
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+ Quadratic model
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+ Cubic model
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+ Inverse of y model
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+ Square root of y model
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+ Inverse of x model
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+ Inverse of y & x model
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+ Square root of model
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+ Cubic root of model
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+ formatted Model Table
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+ Prediction plots
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+ Prediction plots
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+ Fitted plots
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+ Naive effects plots
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+ Coefficients importance plot
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+ Summary of numeric variables
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README.md

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any recognized format but should be a **dataframe** containing two
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columns `Date` and `Case`. The Date is the *day/month/year* the data
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is collected while Case is the variable for forecasting. The Date
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must be in the recognized format, i.e., **YYYY-MM-DD**. The other
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must be in the recognized format i.e. ‘YYYY-MM-DD. The other
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arguments parsed to the function are `MaximumDate`, which is the
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last date Data was collected and `BREAKS`, which is a vector of
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numbers and is used as `knots` in estimating spline polynomials.
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9. `data_transform` is a wrapper for standardizing `data.frame` to make
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the values comparable for estimation and/or visualization.
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10. `estimate_plot` is a function for plotting estimated coefficients of
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a model in their order of significance.
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11. `corplot` is for plotting the correlation matrix.
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## Things the package can do
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The package is capable of
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- Inverse scaled logit for constrained forecast
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- Linear regression and transformations which consists of
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- Linear regression and functional forms which consists of
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- Linear model
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- Linear model with interactions
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- Semilog model
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- Growth model
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- Double Log model
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- Mixed-power model
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- Translog model
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- Quadratic model
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- Cubic model
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- Inverse of y model
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- Square root of y model
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- Inverse of x model
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- Inverse of y & x model
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- Square root of model
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- Cubic root of model
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- formatted Model Table
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- Prediction plots
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- Fitted plots
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- Naive effects plots
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- Coefficients importance plot
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- Summary of numeric variables
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- Summary of character variables

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