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[CodeFactor] Apply fixes to commit 4286113

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This commit is contained in:
codefactor-io
2024-11-11 00:56:50 +00:00
parent 428611315e
commit 697f15cc0c
1 changed files with 6 additions and 6 deletions
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lib/statistics/Granger.cs
+6 -6
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@@ -122,7 +122,7 @@ public sealed class Granger : AbstractBase
X[i, 0] = 1.0; // Constant term
for (int j = 1; j < k; j++)
{
X[i, j] = x[i * (k - 1) + (j - 1)];
X[i, j] = x[(i * (k - 1)) + (j - 1)];
}
}
@@ -190,7 +190,7 @@ public sealed class Granger : AbstractBase
{
// Calculate F-statistic
double numerator = (rss1 - rss2) / p;
double denominator = rss2 / (n - 2 * p - 1);
double denominator = rss2 / (n - (2 * p) - 1);
return numerator / denominator;
}
@@ -199,7 +199,7 @@ public sealed class Granger : AbstractBase
{
// Approximate p-value from F-distribution
// Using a simplified approximation for performance
double v = df2 / (df2 + df1 * f);
double v = df2 / (df2 + (df1 * f));
return Math.Pow(v, df2 / 2.0);
}
@@ -216,7 +216,7 @@ public sealed class Granger : AbstractBase
if (_xValues.Count >= WarmupPeriod && _yValues.Count >= WarmupPeriod)
{
int n = _xValues.Count - Lags;
if (n > 2 * Lags + 1)
if (n > (2 * Lags) + 1)
{
ReadOnlySpan<double> x = _xValues.GetSpan();
ReadOnlySpan<double> y = _yValues.GetSpan();
@@ -224,7 +224,7 @@ public sealed class Granger : AbstractBase
// Prepare data for regression
var yData = y.Slice(Lags, n).ToArray();
var restricted = new double[Lags + 1];
var unrestricted = new double[2 * Lags + 1];
var unrestricted = new double[(2 * Lags) + 1];
// Fit restricted model (only Y lags)
FitOLS(yData, y.Slice(0, n), restricted);
@@ -261,7 +261,7 @@ public sealed class Granger : AbstractBase
if (rss2 > Epsilon)
{
double f = CalculateFStatistic(rss1, rss2, n, Lags);
pValue = FDistributionPValue(f, Lags, n - 2 * Lags - 1);
pValue = FDistributionPValue(f, Lags, n - (2 * Lags) - 1);
}
}
}