cox-stuart趋势检验python
时间: 2023-06-14 16:04:53 浏览: 106
Cox-Stuart趋势检验可以用Python的statsmodels包中的函数实现。以下是一个简单的示例代码:
```python
import pandas as pd
import numpy as np
from statsmodels.tsa.stattools import acf
from statsmodels.tsa.stattools import adfuller
def cox_stuart_test(data, alpha=0.05):
"""
Cox-Stuart trend test for detecting trends in time series data.
"""
n = len(data)
k = int(np.floor(n / 2))
# Calculate the median for each half of the data
med1 = np.median(data[:k])
med2 = np.median(data[k:])
# Calculate the trend statistic
trend_stat = 2 * np.sum(np.sign(data[k:] - data[:k]) != np.sign(med2 - med1))
# Calculate the critical value for the given alpha level
z_alpha = 1.96 if alpha == 0.05 else 2.58 # alpha = 0.05 or 0.01
crit_val = z_alpha * np.sqrt(n - k) / k
# Determine if the trend is significant
if trend_stat > crit_val:
return True # Reject the null hypothesis (trend exists)
else:
return False # Fail to reject the null hypothesis (no trend detected)
# Load example data
df = pd.read_csv('example_data.csv', parse_dates=['date'], index_col='date')
# Test for trend in the 'value' column
trend_detected = cox_stuart_test(df['value'].values)
if trend_detected:
print("A significant trend was detected.")
else:
print("No significant trend was detected.")
```
在这个示例中,我们将数据加载到一个Pandas DataFrame中,并使用`cox_stuart_test()`函数测试`value`列中的趋势。如果趋势是显著的,函数会返回True,否则返回False。