Subscribe to DSC Newsletter
Ted
  • Male
  • New York
  • United States
Share on Facebook
Share

Gifts Received

Gift

Ted has not received any gifts yet

Give a Gift

 

Ted's Page

Latest Activity

Duane Baker liked Ted's blog post Trend Analysis of Fragmented Time Series: Hypothesis Testing Based Adaptive Spline Filtering Method
Nov 6
Mirio De Rosa liked Ted's blog post Trend Analysis of Fragmented Time Series: Hypothesis Testing Based Adaptive Spline Filtering Method
Nov 4
Yanlei Peng liked Ted's blog post Trend Analysis of Fragmented Time Series: Hypothesis Testing Based Adaptive Spline Filtering Method
Nov 3
Vincent Granville liked Ted's blog post Trend Analysis of Fragmented Time Series: Hypothesis Testing Based Adaptive Spline Filtering Method
Nov 3
CD liked Ted's blog post Trend Analysis of Fragmented Time Series: Hypothesis Testing Based Adaptive Spline Filtering Method
Nov 1
AI liked Ted's blog post Trend Analysis of Fragmented Time Series: Hypothesis Testing Based Adaptive Spline Filtering Method
Nov 1
Ted liked Ted's blog post Trend Analysis of Fragmented Time Series: Hypothesis Testing Based Adaptive Spline Filtering Method
Nov 1
Shay Pal liked Ted's blog post Trend Analysis of Fragmented Time Series: Hypothesis Testing Based Adaptive Spline Filtering Method
Nov 1
Ted's blog post was featured

Trend Analysis of Fragmented Time Series: Hypothesis Testing Based Adaptive Spline Filtering Method

Missing data present significant challenges to trend analysis of time series. Straightforward approaches consisting of supplementing missing data with constant or zero values or with linear trends can severely degrade the quality of the trend analysis, which significantly reduces the reliability of the trend analysis. We present…See More
Nov 1
Ted posted a blog post

Trend Analysis of Fragmented Time Series: Hypothesis Testing Based Adaptive Spline Filtering Method

Missing data present significant challenges to trend analysis of time series. Straightforward approaches consisting of supplementing missing data with constant or zero values or with linear trends can severely degrade the quality of the trend analysis, which significantly reduces the reliability of the trend analysis. We present…See More
Nov 1
Ted updated their profile photo
Oct 28
Ted liked CD's blog post From social media to public health surveillance: Word embedding based clustering method for twitter classification
Oct 27

Profile Information

Short Bio
Associate Professor
Field of Expertise
Analytics, Data Integration, Visualization, BI, Other, Big Data, Data Science
Professional Status
Professor
Years of Experience:
12
Industry:
education
Your Job Title:
Associate Professor
Interests:
Finding a new position, Networking, New venture, Recruiting, Other

Ted's Blog

Trend Analysis of Fragmented Time Series: Hypothesis Testing Based Adaptive Spline Filtering Method

Posted on October 31, 2017 at 7:30pm 0 Comments

Missing data present significant challenges to trend analysis of time series. Straightforward approaches consisting of supplementing missing data with constant or zero values or with linear trends can severely degrade the quality of the trend analysis, which significantly reduces the reliability of the trend analysis. …

Continue

Comment Wall

You need to be a member of Data Science Central to add comments!

Join Data Science Central

  • No comments yet!
 
 
 

Follow Us

Videos

  • Add Videos
  • View All

Resources

© 2017   Data Science Central   Powered by

Badges  |  Report an Issue  |  Privacy Policy  |  Terms of Service