connects #2118

This pull request introduces significant enhancements to the regression model selection workflow, focusing on improved date range handling, validation, and error messaging for user-defined models. The changes add new properties to track both start and end dates for regression models, implement comprehensive validation to ensure data completeness and correct date ranges, and update the UI to provide clear feedback to users.

Key changes include:

Regression Model Date Range Enhancements

• Added new properties to AnalysisGroup and related interfaces to support both start and end months and years for regression models, enabling more flexible and accurate date range selection. (src/app/models/analysis.ts, src/app/models/idbModels/analysisItem.ts)
• Updated initialization and default value logic to ensure new and existing analysis groups have these date fields populated appropriately.

Validation and Error Handling

• Implemented comprehensive validation in RegressionModelMenuComponent to check for:
  • Valid date ranges (end date after start date)
  • Minimum of 12 months selected
  • Presence of all required meter and predictor data within the selected range
  • Updated error tracking in GroupErrors and validation service to support new date fields.

User Interface Improvements

• Enhanced the regression model selection UI to:
  • Display new input fields for selecting model start/end months and years
  • Show specific error messages when validation fails (e.g., invalid date range, insufficient data, missing readings)
  • Disable model evaluation when validation errors are present

Data Filtering and Model Inspection

• Updated logic in the user-defined model inspection component to filter and display analysis data based on the full selected date range, rather than just a single year/month.

Error State Propagation

• Ensured new error states for missing start/end months and years are correctly propagated and checked throughout the application, improving robustness and user feedback.

These changes collectively improve the accuracy, reliability, and user experience of the regression model selection and validation process.