[Gretl-users] Removing outliers in Panel regression

Hi, I'm looking at panel regression, and one of the assumptions in regression is to remove outliers. My data has a lot of outliers, and it impacts my residuals which are definitely not normal. I'm wondering if there is an easy way to remove the outliers? Thank you Alison Alison Loddick BSc MSc PGCE CStat Learning Development Tutor (Mathematics and Statistics) Library and Learning Services DDI +44 (0)1604 893502 [https://static.hobsons.co.uk/northampton/usermedia/Staff%20News/2017/New%...] northampton.ac.uk University of Northampton, Waterside Campus, University Road, Northampton, NN1 5PH United Kingdom University of Northampton: Transforming Lives and Inspiring Change www.northampton.ac.uk This e-mail is private and may be confidential and is for the intended recipient only. If you are not the intended recipient you are strictly prohibited from using, printing, copying, distributing or disseminating this e-mail or any information contained in it. We virus scan all E-mails leaving The University of Northampton but no warranty is given that this E-mail and any attachments are virus free. You should undertake your own virus checking. The right to monitor E-mail communications through our networks is reserved by us. Disclaimer The information contained in this communication from the sender is confidential. It is intended solely for use by the recipient and others authorized to receive it. If you are not the recipient, you are hereby notified that any disclosure, copying, distribution or taking action in relation of the contents of this information is strictly prohibited and may be unlawful. This email has been scanned for viruses and malware, and may have been automatically archived by Mimecast, a leader in email security and cyber resilience. Mimecast integrates email defenses with brand protection, security awareness training, web security, compliance and other essential capabilities. Mimecast helps protect large and small organizations from malicious activity, human error and technology failure; and to lead the movement toward building a more resilient world. To find out more, visit our website.