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1001 Solutions
Published in Jaakko Astola, Pauli Kuosmanen, Fundamentals of Nonlinear Digital Filtering, 2020
Jaakko Astola, Pauli Kuosmanen
where X* is the sample we are making decision of, X(k+1) is the median inside the moving window, and s is some scale estimate. The simplest scale estimate is the sample variance, but it is a very nonrobust estimate. The median of the absolute deviations from the median, MAD, s=1.483MED{|Xi−MED{Xi}|}
Measures of Dispersion and Shape
Published in Alan R. Jones, Probability, Statistics and Other Frightening Stuff, 2018
Unfortunately, there is no special function within Microsoft Excel that calculates the Median Absolute Deviation, and we will have to resort to long-hand methods. (Was that the sound of someone yawning?)
The recommendation for learners to be provided with control over their feedback schedule is questioned in a self-controlled learning paradigm
Published in Journal of Sports Sciences, 2022
Zachary D. Yantha, Brad McKay, Diane M. Ste-Marie
Univariate outliers were identified using the median absolute deviation (MAD) method (Leys et al., 2013). We searched for outliers only in the post-test phase, given that the main interest is the effects of the independent variable on learning (Schmidt & Bjork, 1992). More specifically, to search for outliers, we averaged the two post-test scores (retention and transfer) together and then applied the MAD method using the very conservative criterion value (i.e., of 3 times the MAD) for each dependent variable. Specifically, the MAD method that was employed involved using the group median to calculate the MAD and then taking the defined rejection criterion, in this case 3, and multiplying it by the MAD. The last step requires taking the product and ± it by the group median to define upper and lower limits in error for identifying outliers. We identified two univariate outliers within the post-test data for MRE and no outliers for BVE. One outlier was from the coach-yoked group (M = 63.40 cm, Distance from the Upper Criterion Limit = 5.75 cm, 0 putts in the post-test hit the backstop) and one from the TY group (M = 83.96 cm, Distance from the Upper Criterion Limit = 2.86 cm, 14 putts in the post-test hit the backstop). Outliers were removed from the primary post-test MRE analyses.
Evaluation and augmentation of traffic data including Bluetooth detection system on arterials
Published in Journal of Intelligent Transportation Systems, 2021
Yaobang Gong, Mohamed Abdel-Aty, Juneyoung Park
The travel times and space mean speeds calculated by the aforementioned method have some noise. For instance, several extreme long travel times may indicate that from the non-motorized mode. Thus, a Moving Median Absolute Deviation filtering algorithm was adopted to eliminate outliers. First, the median of all space mean speed readings with a 9-min moving window is calculated (Bhaskar, Qu, & Chung, 2015). And the upper bound value (UBV) and lower bound value (LBV) are defined as where and is the UBV and LBV; Med is the median space mean speed of the speed observations among the moving time window; MAD is the median absolute deviation from the Med; is the standard deviation from MAD. value was decided considering the variance level of speed data. A smaller gives a higher confidence of the estimation, yet several valid data might be filtered out if the variance is relatively large. In this study, 1.5 is selected as the value.
A visual–textual fused approach to automated tagging of flood-related tweets during a flood event
Published in International Journal of Digital Earth, 2019
Xiao Huang, Cuizhen Wang, Zhenlong Li, Huan Ning
Due to the short acquisition period of the test dataset (15th August to 15th September) and the ubiquitous existence of extreme values, we apply a modified Z score to statistically evaluate the sensitiveness for each word. The modified Z score measures the outlier strength or how much a score differs from its median instead of mean, hence less influenced by extreme values. It is computed using the Median Absolute Deviation (MAD), modified from Iglewicz and Hoaglin (1993):where is a constant of 0.6745, denotes the occurrence of a certain word on day . denotes the sample median and is the modified Z score on day . MAD is calculated by taking the median of the absolute deviations from the median: