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Curve and Surface Fitting. Curve fitting is one of the most powerful and most widely used analysis tools in Origin. Curve fitting examines the relationship between one or more predictors (independent variables) and a response variable (dependent variable), with the goal of defining a 'best fit' model of the relationship. Twelve South's Curve is an elevated desktop stand for Apple MacBook, MacBook Air & MacBook Pro. Boost the performance of your MacBook with improved ventilation and better cooling. Avoid tech neck or neck pain by raising your laptop screen to a more comfortable viewing height.
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Summary
https://hiregenerous.weebly.com/blog/best-cf-card-reader-for-mac. Forecasts the future values of each location of a space-time cube using curve fitting.
The tool fits a parametric curve to each location in the Input Space Time Cube and forecasts the time series by extrapolating this curve to future time steps. The curves can be linear, parabolic, S-shaped (Gompertz), or exponential. You can use the same curve type at each location of the space-time cube or allow the tool to set which curve type best fits each location.
Usage
- This tool accepts netCDF files created by the Create Space Time Cube By Aggregating Points, Create Space Time Cube From Defined Features, and Create Space Time Cube from Multidimensional Raster Layer tools.
- Compared to other forecasting tools in the Time Series Forecasting toolset, this tool is the most straightforward, and it is most appropriate for time series that follow a predictable trend that does not display strong seasonality. If your data follows a complex trend or displays strong seasonal cycles, use other forecasting tools. https://printerintensive779.weebly.com/blog/smart-tv-app-mac-address.
- Multiple forecasted space-time cubes can be compared and merged using the Evaluate Forecasts by Location Imo download for mac os x. tool. This allows you to create multiple forecast cubes using different forecasting tools and parameters, and the tool will identify the best forecast for each location using either Forecast root mean square error (RMSE) or Validation RMSE.
- Mac apps not showing. For each location in the Input Space Time Cube, the tool builds two models that serve different purposes.
- Forecast model—This model is used to forecast future values of the space-time cube by fitting a curve to the values of the time series and extrapolating this curve to future time steps. The fit of the forecast model to the values of the space-time cube is measured by the Forecast RMSE value.
- Validation model—This model is used to validate the forecast model and test how accurately it can forecast future values. If a number greater than 0 is specified for the Number of Time Steps to Exclude for Validation parameter, this model is fitted to the time steps that were not excluded and is used to forecast the values of the time steps that were excluded. This allows you to see how well the chosen curve type can forecast future values. The fit of the forecasted values to the excluded values is measured by the Validation RMSE value.
- File format for mac and pc. The Auto-Detect option of the Curve Type parameter will fit all four curve types at each location and identify the one with the smallest Validation RMSE. If no time steps are excluded for validation, the curve with the smallest Forecast RMSE is used.
- The Output Features will be added to the Contents pane with rendering based on the final forecasted time step.
- This tool creates geoprocessing messages and pop-up charts to help you understand and visualize the forecast results. The messages contain information about the structure of the space-time cube and summary statistics of the RMSE values. Clicking a feature using the Explore navigation tool displays a line chart in the Pop-up pane showing the values of the space-time cube, the curve used to forecast, and the forecasted values for that location.
- Deciding how many time steps to exclude for validation is an important choice. The more time steps are excluded, the fewer time steps remain to estimate the validation model. However, if too few time steps are excluded, the Validation RMSE will be estimated using a small amount of data and may be misleading. It is recommended that you exclude as many time steps as possible while still maintaining sufficient time steps to estimate the validation model. It is also suggested that you withhold at least as many time steps for validation as the number of time steps you intend to forecast, if your space-time cube has enough time steps to allow this.
Syntax
Parameter | Explanation | Data Type |
The netCDF cube containing the variable you want to forecast to future time steps. This file must have an .nc file extension and must have been created using the Create Space Time Cube By Aggregating Points, Create Space Time Cube From Defined Locations, or Create Space Time Cube From Multidimensional Raster Layer tools. | File | |
analysis_variable | The numeric variable in the netCDF file that will be forecasted to future time steps. | String |
Best personal accounting app for mac. The output feature class of all locations in the space-time cube with forecasted values stored as fields. The layer displays the forecast for the final time step and contains pop-ups charts showing the time series and forecasts for each location. | Feature Class | |
output_cube | A new space-time cube (.nc file) containing the values of the input space-time cube with the forecasted time steps appended. The Visualize Space Time Cube in 3D tool can be used to see all of the observed and forecasted values simultaneously. | File |
number_of_time_steps_to_forecast | A positive integer specifying the number of time steps to forecast. This value cannot be larger than 50 percent of the total time steps in the input space-time cube. The default value is one time step. | Long |
curve_type | Adobe flash player alternative for mac. Specifies the curve type that will be used to forecast the values of the input space-time cube.
| String |
(Optional) | The number of time steps at the end of each time series to exclude for validation. The default value is 10 percent (rounded down) of the number of input time steps, and this value cannot be larger than 25 percent of the number of time steps. Provide the value 0 to not exclude any time steps. | Long |
Code sample
CurveFitForecast example 1 (Python window)Curve Fitting App Mac Pro
The following Python script demonstrates how to use the CurveFitForecast tool:
CurveFitForecast example 2 (stand-alone script)The following Python script demonstrates how to use the CurveFitForecast tool to forecast population:
Environments
Licensing information
- Basic: Yes
- Standard: Yes
- Advanced: Yes