rpy2版本== 2.9.4

OS == Windows

我正在遍历以下代码并使用rpy2，以便可以使用R的rugarch库。

    for stock in lrets.columns:
        garch_spec = rugarch.ugarchspec(mean_model=robjects.r('list(armaOrder = c(0,0))'),variance_model=robjects.r('list(garchOrder=c(1,1))'),distribution_model='std')

        # Used to convert training set to R list for model input
        numpy2ri.activate()
        # Train R GARCH model on returns as %
        garch_fitted = rugarch.ugarchfit(spec=garch_spec,data=lrets.loc[:,stock].values)
        numpy2ri.deactivate()

        # Model's fitted standard deviation values
        # Revert previous multiplication by 100
        fitted = 0.01 * np.array(garch_fitted.slots['fit'].rx2('sigma')).flatten()
        df['forecast_std_'+stock] = fitted

        # Forecast using R GACRH model
        garch_forecast = rugarch.ugarchforecast(garch_fitted,n_ahead=forecast_horizon)

        # Model's forecasted standard deviation values
        # Revert previous multiplication by 100
        forecast = 0.01 * np.array(garch_forecast.slots['forecast'].rx2('sigmaFor')).flatten()
        forecast = pd.DataFrame(data={stock: forecast},index=forecasts_dates)
        forecasts_std_into_future_df = pd.concat([forecasts_std_into_future_df,forecast],axis=1,join='outer')

但是，代码会在不同的循环迭代中随机崩溃，并出现rpy2.rinterface.RNULLType错误，例如该错误可能会出现在第一个循环中，但是在我再次运行代码之后，在接下来的几次迭代中它似乎还不错。我不确定这是怎么回事，因为我是rpy2的新手，并不熟悉R。