The phrase "regression into" is correct and usable in written English.
It is typically used to describe a return to a previous state or condition. Example: After a series of successful advancements, the company's recent financial struggles have led to a regression into old, inefficient business practices.
Specifically, as described in the FSL webpage (http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/DualRegression), "for each subject, the group-average set of spatial maps is regressed (as spatial regressors in a multiple regression) into the subject's 4D space-time dataset.
Next, those timeseries [sic] are regressed (as temporal regressors, again in a multiple regression) into the same 4D dataset, resulting in a set of subject-specific spatial maps, one per group-level spatial map".
One of the most common downfalls of similar retrospectives is a regression into smug romanticising, breeding contemporary complacency.
A woman Steger meets in Ljubljana asks him whether he has ever experienced "regression into past lives", and tries to persuade him that they have met before.
The cardinals should not forget what happened in Ireland, when the church bolted sexual regression into the country's constitution during the 1980s – only to face a terrible comeuppance.
Using an apocryphal quote from Frederich Engels, Rosa Luxemburg once wrote: "Bourgeois society stands at the crossroads, either transition to socialism or regression into barbarism".
"You see this regression back into childhood".
First, we took alternative estimation techniques like differences in differences or regression discontinuity into account.
This article introduces the least squares support vector machine for regression (LSSVR) into reliability analysis to overcome these shortcomings.
Hence, they present a unified framework for binary recursive partitioning which embeds tree-structured regression models into a well-defined theory of conditional inference procedures.
Differing from the common methods above, this paper provides a new idea that brings the support vector regression (SVR) into the wall parameter estimation (WPE) problem.
