Add TEMA (Triple Exponential Moving Average) implementation and validation tests

- Implemented TEMA calculation in QuanTAlib with O(1) update complexity.
- Added validation tests for TEMA against Skender, TA-Lib, and Tulip indicators.
- Updated documentation for TEMA, including its mathematical foundation and usage examples.
- Enhanced existing tests for other indicators (TRIMA, WMA) to generate more records.
- Adjusted benchmark tests to include DEMA and TEMA comparisons.
- Refactored code for better readability and performance, including zero-allocation Span API.

lib/averages/sma/Sma.Validation.Tests.cs

@@ -19,9 +19,9 @@ public class SmaValidationTests
     {
         _output = output;
 
-        // 1. Generate 1000 records using GBM feed
+        // 1. Generate 5000 records using GBM feed
         var gbm = new GBM(startPrice: 100.0, mu: 0.05, sigma: 0.2);
-        _bars = gbm.Fetch(1000, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
+        _bars = gbm.Fetch(5000, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
 
         // 2. Extract Close TSeries
         _data = _bars.Close;

lib/averages/sma/Sma.cs

@@ -11,27 +11,18 @@ namespace QuanTAlib;
 /// SMA: Simple Moving Average
 /// </summary>
 /// <remarks>
-/// SMA calculates the arithmetic mean of the last N values.
-/// Uses a RingBuffer for storage and manual running sum for O(1) operations.
+/// SMA calculates the arithmetic mean of the last n values.
+/// Uses a RingBuffer for storage and manual running sum for O(1) complexity per update.
 ///
-/// Key characteristics:
-/// - Equal weighting of all values in the period
-/// - No lag bias - responds equally to all values in window
-/// - Smooth output with good noise reduction
-/// - O(1) time complexity for both update and bar correction
-/// - O(1) space complexity for state save/restore (scalars only)
+/// Calculation:
+/// SMA = (P_n + P_(n-1) + ... + P_1) / n
 ///
-/// Calculation method:
-/// SMA = Sum(values in period) / period
+/// O(1) update:
+/// S_new = S_old - oldest + newest
+/// SMA = S_new / n
 ///
-/// Bar correction (isNew=false):
-/// - Restores to state after last isNew=true
-/// - Then replaces the last value with new correction value
-/// - All O(1) using scalar state
-///
-/// Sources:
-/// - https://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:moving_averages
-/// - https://www.investopedia.com/terms/s/sma.asp
+/// IsHot:
+/// Becomes true when the buffer is full (period samples processed).
 /// </remarks>
 [SkipLocalsInit]
 public sealed class Sma