Seasonal Adjustment in R: Time Series Decomposition

In R language, the decompose() function can be used to seasonally adjust and decompose trends. This function breaks down time series data into trend, seasonal, and random components.

Here is an example code demonstrating how to use the decompose() function for seasonal adjustment and trend decomposition:

# 创建一个时间序列数据
ts_data <- ts(my_data, frequency = 12)

# 对时间序列数据进行趋势分解
decomposed_ts <- decompose(ts_data)

# 提取出趋势、季节性和随机成分
trend <- decomposed_ts$trend
seasonal <- decomposed_ts$seasonal
random <- decomposed_ts$random

# 绘制趋势、季节性和随机成分的图表
plot(decomposed_ts)

In this code, the time series data is first converted into a time series object, then decomposed using the decompose() function. Finally, by extracting the trend, seasonal, and random components, it can be visualized for display.

I hope this example will help you with seasonal adjustments and trend decomposition.