UPDATE: Implement FTEST function

base/src/functions/statistical/fisher.rs

@@ -1,6 +1,7 @@
 use statrs::distribution::{Continuous, ContinuousCDF, FisherSnedecor};
 
 use crate::expressions::types::CellReferenceIndex;
+use crate::functions::statistical::t_dist::sample_var;
 use crate::{
     calc_result::CalcResult, expressions::parser::Node, expressions::token::Error, model::Model,
 };
@@ -296,4 +297,122 @@ impl Model {
 
         CalcResult::Number(x)
     }
+
+    // F.TEST(array1, array2)
+    pub(crate) fn fn_f_test(&mut self, args: &[Node], cell: CellReferenceIndex) -> CalcResult {
+        if args.len() != 2 {
+            return CalcResult::new_args_number_error(cell);
+        }
+
+        let values1_opts = match self.evaluate_node_in_context(&args[0], cell) {
+            CalcResult::Range { left, right } => match self.values_from_range(left, right) {
+                Ok(v) => v,
+                Err(error) => return error,
+            },
+            CalcResult::Array(a) => match self.values_from_array(a) {
+                Ok(v) => v,
+                Err(error) => {
+                    return CalcResult::new_error(
+                        Error::VALUE,
+                        cell,
+                        format!("Error in first array: {:?}", error),
+                    );
+                }
+            },
+            _ => {
+                return CalcResult::new_error(
+                    Error::VALUE,
+                    cell,
+                    "First argument must be a range or array".to_string(),
+                );
+            }
+        };
+
+        // Get second sample as Vec<Option<f64>>
+        let values2_opts = match self.evaluate_node_in_context(&args[1], cell) {
+            CalcResult::Range { left, right } => match self.values_from_range(left, right) {
+                Ok(v) => v,
+                Err(error) => return error,
+            },
+            CalcResult::Array(a) => match self.values_from_array(a) {
+                Ok(v) => v,
+                Err(error) => {
+                    return CalcResult::new_error(
+                        Error::VALUE,
+                        cell,
+                        format!("Error in second array: {:?}", error),
+                    );
+                }
+            },
+            _ => {
+                return CalcResult::new_error(
+                    Error::VALUE,
+                    cell,
+                    "Second argument must be a range or array".to_string(),
+                );
+            }
+        };
+
+        let values1: Vec<f64> = values1_opts.into_iter().flatten().collect();
+        let values2: Vec<f64> = values2_opts.into_iter().flatten().collect();
+
+        let n1 = values1.len();
+        let n2 = values2.len();
+
+        // If fewer than 2 numeric values in either sample -> #DIV/0!
+        if n1 < 2 || n2 < 2 {
+            return CalcResult::new_error(
+                Error::DIV,
+                cell,
+                "F.TEST requires at least two numeric values in each sample".to_string(),
+            );
+        }
+
+        let v1 = sample_var(&values1);
+        let v2 = sample_var(&values2);
+
+        if v1 <= 0.0 || v2 <= 0.0 {
+            return CalcResult::new_error(
+                Error::DIV,
+                cell,
+                "Variance of one sample is zero in F.TEST".to_string(),
+            );
+        }
+
+        // F ratio: larger variance / smaller variance
+        let mut f = v1 / v2;
+        let mut df1 = (n1 - 1) as f64;
+        let mut df2 = (n2 - 1) as f64;
+
+        if f < 1.0 {
+            f = 1.0 / f;
+            std::mem::swap(&mut df1, &mut df2);
+        }
+
+        let dist = match FisherSnedecor::new(df1, df2) {
+            Ok(d) => d,
+            Err(_) => {
+                return CalcResult::new_error(
+                    Error::NUM,
+                    cell,
+                    "Invalid parameters for F distribution in F.TEST".to_string(),
+                );
+            }
+        };
+
+        // One-tailed right-tail probability
+        let tail = 1.0 - dist.cdf(f);
+        // F.TEST is two-tailed: p = 2 * tail (with F >= 1)
+        let mut p = 2.0 * tail;
+
+        // Clamp tiny FP noise
+        if p < 0.0 && p > -1e-15 {
+            p = 0.0;
+        }
+        if p > 1.0 && p < 1.0 + 1e-15 {
+            p = 1.0;
+        }
+
+        CalcResult::Number(p)
+    }
 }