The first retrospective monograph on internationally acclaimed Danish artist's collective Superflex, "An Artist with 6 Legs" catalogues the group's work from 1993 to 2013. The first major museum retrospective for this group--known for their participatory, politically engaged projects which they call "tools"--is appropriately unconventional, comprised of eight individual retrospectives curated by Eungie Joo, Yuko Hasegawa, Toke Lykkeberg, Daniel McClean and Lisa Rosendahl, Adriano Pedrosa, Agustin Perez Rubio, Hilde Teerlinck and Rirkrit Tiravanija. Kunsthal Charlottenborg also signed a contract prohibiting the institution, the artists or the curators from mentioning the group by name during the exhibition's run--hence the replacement of the name "Superflex" with a black bar or the characters "XXXXXXX throughout the catalogue. "An Artist with 6 Legs" is both conceptual provocation and an essential reference.

The mixed-media collages of Kirstine Roepstorff (born 1972) spill over with messy glee. Over the past decade, Roepstorff has built up a large body of collage work that stages and dismantles the imagery of our times, drawing out themes of disinformation, media theory and feminism. She often coheres her collage narratives through archetypal characters, which come to the fore in her new mechanical theater installation, "Stille Teater" ("Quiet Theater"), documented here alongside essays and an interview with the artist.

This advanced textbook explores small area estimation techniques, covers the underlying mathematical and statistical theory and offers hands-on support with their implementation. It presents the theory in a rigorous way and compares and contrasts various statistical methodologies, helping readers understand how to develop new methodologies for small area estimation. It also includes numerous sample applications of small area estimation techniques. The underlying R code is provided in the text and applied to four datasets that mimic data from labor markets and living conditions surveys, where the socioeconomic indicators include the small area estimation of total unemployment, unemployment rates, average annual household incomes and poverty indicators. Given its scope, the book will be useful for master and PhD students, and for official and other applied statisticians.

This advanced textbook explores small area estimation techniques, covers the underlying mathematical and statistical theory and offers hands-on support with their implementation. It presents the theory in a rigorous way and compares and contrasts various statistical methodologies, helping readers understand how to develop new methodologies for small area estimation. It also includes numerous sample applications of small area estimation techniques. The underlying R code is provided in the text and applied to four datasets that mimic data from labor markets and living conditions surveys, where the socioeconomic indicators include the small area estimation of total unemployment, unemployment rates, average annual household incomes and poverty indicators. Given its scope, the book will be useful for master and PhD students, and for official and other applied statisticians.