• Detrend（去除线性趋势）— 从仿真，预测以及误差数据中移除线性趋势。此选项允许检查实际数据的变化是否仍然被仿真或预测输出所捕获。例如，你观察到你的仿真或预测数据偏离实际数据，但它们的变化似乎彼此一致。你可以通过消除仿真或预测数据的长趋势来检查这个假设。当选中detrend复选框时，将计算一个线性回归模型。且将从仿真数据中减去线性回归模型的输出。Detrend选项适用于FIR，F2P和PAR模型的输出。目前线性回归模型不对每个数据段进行计算，但对所有数据执行计算。注意若当你在应用detrend之后仍然观察到一些或所有数据段中有漂移，这可能意味着不同的数据段间的线性趋势有不同。此外请确认将空数据点标记为错误段，以避免不必要的坏拟合。
下面两个图显示了去除线性趋势功能的应用。第一张图显示FIR，F2P和PAR模型的输出偏离了实际数据。在这个例子中，输入/输出模型是斜坡模型。第二张图显示了原始数据和去除线性趋势仿真数据之间的比较。在去除FIR和F2P模型的线性趋势之后，仍然可以合理地捕获原始数据的变化。

仿真窗口字段
Segments（数据段）：包含所有工作区数据段的下拉列表。
Input（输入）：在预测图上部子图中的去趋势输入位号。
Output（输出）：输出及其预测值绘图。
Sample Time（采样时间）：当前光标位置的采样时间。
Simulation/Error（仿真/误差）：这些单选按钮用于控制图像是显示仿真结果还是误差结果。
Detrend（去除线性趋势）：若选中此项，拟合输出（仿真，预测，差分数据，误差或所有这些选项的组合）将被去除线性趋势。
Difference（差分）：若选中此项，输出和拟合输出的时间序列会有差异。差分对于评估斜坡模型的拟合优度非常有用。
图例表
Show（显示）：若选中此项，相应的模型预测将显示在预测图上。
Color（颜色）：双击以修改预测图线的颜色;此线条颜色也对应于overlay和FIR fit窗口中的线条颜色。

原文：
**• Detrend **– Remove linear trend from simulation, prediction as well as the error data. This option allows one to check whether the variations of the actual data are still captured in the simulated or predicted output. For example, you observe that your simulation or prediction data drifts away from the actual data but their variations seem to agree with each other. You can check this hypothesis by detrending the simulation or prediction data. When the detrend checkbox is checked, a linear regression model will be calculated. The output of the the linear regression model will be subtracted from the simulation data. Detrend option applies to the output of the FIR, F2P, and PAR models. Currently, the linear regression model is not calculated for each data segment, but calculated for all data. Keep that in mind when you still observe drifts in some or all segments after applying detrend as it may suggest that the linear trends differ from one segment to the other. Also, ensure that you mark empty data points as bad segments to avoid unnecessary bad fits.
The two figures below show the application of the detrend feature. The top figure shows that the outputs of FIR, F2P, and PAR models drift away from the actual data. In this example, the input/output models are ramp models. The figure at the bottom shows the comparison between the original data and the detrended simulation data. Variations of the original data can still be reasonably captured after linear trends from FIR and F2P models are removed.

Simulation Window Fields
Segments: Drop down list with all the workspace segments.
**Input: **Input tag trended in upper subplot of prediction plot.
**Output: **Output and its predictions to be plotted.
Sample Time: Sample time of current cursor position.
Simulation/Error: These radio buttons control whether the plots show simulation results or error results.
Detrend:If checked, the fit output (either simulated, predicted, differenced data, error or the combination of all these options) will be detrended.
Difference: If checked, the time series of the output and the fit output are both differenced. Differencing is very useful for assessing the goodness of fit for ramp models.
Legend Table
Show: If checked, the corresponding model prediction is shown on the predictions plot.
Color:Double-click to modify the prediction plot line color; this line color also corresponds to the line colors in the overlay and FIR fit windows.

2016.11.23