diff --git a/pyfacts/pyfacts.py b/pyfacts/pyfacts.py
index fdeff56..fd41153 100644
--- a/pyfacts/pyfacts.py
+++ b/pyfacts/pyfacts.py
@@ -805,7 +805,11 @@ class TimeSeries(TimeSeriesCore):
         return statistics.mean(self.values)
 
     def transform(
-        self, to_frequency: Literal["W", "M", "Q", "H", "Y"], method: Literal["sum", "mean"], eomonth: bool = False
+        self,
+        to_frequency: Literal["W", "M", "Q", "H", "Y"],
+        method: Literal["sum", "mean"],
+        eomonth: bool = False,
+        anchor_date=Literal["start", "end"],
     ) -> TimeSeries:
         """Transform a time series object into a lower frequency object with an aggregation function.
 
@@ -850,18 +854,21 @@ class TimeSeries(TimeSeriesCore):
             ensure_coverage=True,
             eomonth=eomonth,
         )
-        prev_date = dates[0]
+        # prev_date = dates[0]
 
         new_ts_dict = {}
-        for date in dates[1:]:
-            cur_data = self[(self.dates >= prev_date) & (self.dates < date)]
+        for idx, date in enumerate(dates):
+            if idx == 0:
+                cur_data = self[self.dates <= date]
+            else:
+                cur_data = self[(self.dates <= date) & (self.dates > dates[idx - 1])]
             if method == "sum":
                 value = sum(cur_data.values)
             elif method == "mean":
                 value = cur_data.mean()
 
-            new_ts_dict.update({prev_date: value})
-            prev_date = date
+            new_ts_dict.update({date: value})
+            # prev_date = date
 
         return self.__class__(new_ts_dict, to_frequency.symbol)