我有一个xts对象，每小时价格，并希望看看非农就业人数（NFP）经济数据发布后的价格行为。 NFP在每个月的第一个星期五举行。所以我想创建一个子集，其中包含每月第一个星期五和星期一之后的价格。为实现这一目标，我查看了这个问题Get the 4th Wednesday of each November in R，并将以下代码放在一起：
library(xts)
DATSxts <- structure(c(1069.4, 1070.7, 1070.4, 1070.3, 1068.7, 1068.7, 1069.4, 1069.7, 1069.5, 1068.1, 1069.3, 1069.2, 1069.3, 1070.7, 1070.9, 1070.7, 1070.8, 1070.5, 1070.5, 1069.7, 1068.9, 1070.2, 1067.3, 1067.8, 1067.9, 1061.7, 1060.8, 1061.7, 1060.9, 1060.2, 1060.9, 1061, 1060.3, 1061.2, 1061.9, 1062, 1061.9, 1062.5, 1062.3, 1062.3, 1062, 1062.7, 1063, 1062, 1062.6, 1062.4, 1061.8, 1058.9, 1061.5, 1062.4, 1061.4, 1060.9, 1062, 1060.6, 1059.4, 1060.5, 1061.3, 1063.1, 1064.6, 1063.5, 1064.3, 1063.7, 1065.3, 1068.7, 1069.8, 1071.3, 1072.8, 1073.8, 1072.9, 1072.7, 1072.6, 1078.8, 1080.6, 1078.2, 1073.7, 1076.4, 1075.2, 1075.4, 1075.4, 1074.7, 1073.2, 1076, 1076.5, 1076.2, 1077.1, 1077.6, 1078.5, 1079.1, 1077, 1077, 1078.1, 1077.7, 1080, 1079.7, 1075.6, 1077.2, 1077.2, 1080, 1080, 1078.8, 1079, 1078.9, 1077.8, 1078, 1077.7, 1076.1, 1077, 1078.4, 1078.6, 1079.5, 1080.5, 1082.1, 1083.3, 1083.5, 1085.6, 1085.2, 1088.8, 1085.1, 1090.5, 1088, 1091.1, 1091.4, 1094.3, 1094.4, 1094.2, 1094.1, 1093.1, 1093.1, 1097.6, 1098.7, 1098.2, 1100.1,
1099.4, 1100.1, 1097.6, 1096.1, 1097, 1096.4, 1098.5, 1100.8, 1101.8, 1106.4, 1103.5, 1106.4, 1109.5, 1108.7, 1110.4, 1109.8, 1109.5, 1109.9, 1109.1, 1104.3, 1105.2, 1104.1, 1103.5, 1104, 1102.9, 1101.7, 1099.8, 1096.8, 1098.6, 1100, 1100.1, 1100, 1101.9, 1103.7, 1103.8, 1101.2, 1098.9, 1103.1, 1104.6, 1104.9, 1107.2, 1107.1, 1106.1, 1105.2, 1104.5, 1104.4, 1105.6, 1107.4, 1106.7, 1100.8, 1100, 1104.4, 1103.4, 1104, 1101.4, 1102, 1100, 1098.9, 1099.6, 1097.3, 1096.8, 1095.4, 1094.5, 1096.3, 1095.4, 1095.8, 1096, 1097.4, 1098.4, 1096.3, 1095, 1095.4, 1096.9, 1095.4, 1092.3, 1091.6, 1087.8, 1089, 1085.8, 1088.8, 1086.8, 1086.8, 1087.5, 1090.3, 1090, 1086.8, 1087.1, 1086.6, 1086.2, 1085, 1084.4, 1083.9, 1085.7, 1085.9, 1082.9, 1082.7, 1081.7, 1082.7, 1083.3, 1083.2, 1082.2, 1088.7, 1089.5, 1092.4, 1091.6, 1093, 1094.4, 1095.2, 1094.1, 1095.8, 1094.5, 1093.1, 1093.7, 1093.1, 1095.4, 1092.3, 1091.5, 1089.1, 1092.5, 1092.4, 1091.4, 1092.3, 1086.1, 1084.8, 1088.7, 1082.9, 1082.6, 1078.4, 1073.6, 1076.9, 1077.6, 1079.1, 1077.7, 1078.6, 1078.8, 1080.4, 1081.2, 1081.5, 1081.1, 1083.6, 1084.9, 1084.2, 1083.9, 1081.3, 1082.4, 1084.6, 1094.6, 1094.1, 1091.1, 1090.7, 1090.8, 1090.3, 1089.3, 1088.8, 1089.4, 1091, 1091.5, 1091.9, 1093.3, 1092.4, 1093.1, 1090.9, 1090.6, 1091, 1089.3, 1091.8, 1091.2, 1090.5, 1091, 1090.6, 1089.8, 1089.7, 1090.1, 1089.7, 1089.3, 1089.1, 1086.4, 1090.6, 1090.3, 1089, 1089.3, 1089.5, 1090.8, 1093.3, 1089.5, 1087.8, 1084.7, 1085.3, 1086.7, 1086.8, 1086.9, 1087.7, 1090.1, 1090.8, 1088.3, 1087.9, 1088.1, 1088.6, 1090.1, 1092.2, 1091.6, 1093.3, 1093.3, 1091.9, 1092.7, 1094.8, 1096.3, 1094.1, 1095.5, 1095.9, 1102.5, 1100.5, 1101.9, 1102.8, 1104.3, 1106.8, 1105.6, 1104.5, 1102.7, 1101.8, 1100.4, 1099.7, 1100.7, 1100.3, 1100.9, 1103, 1104.3, 1103.8, 1104.1, 1101.4, 1099.7, 1098.3, 1100.2, 1100.6, 1098.6, 1097.2, 1095.7, 1095.4, 1096, 1101.8, 1101.6, 1103.5, 1102.2, 1101.7, 1100.3, 1100.4, 1100.1, 1102.1, 1100.6, 1099.8, 1099.5, 1097.8, 1096.4, 1098.1, 1098.7, 1099.1, 1098.9, 1096.2, 1097.3, 1101.3, 1100, 1099, 1097, 1097.8, 1098.8, 1099, 1099.1, 1099.3, 1101.3, 1102.1, 1102.9, 1103.1, 1101.9, 1102.3, 1105.2, 1104.3, 1105.7, 1105.1, 1107.5, 1105.4, 1107.9, 1107.4, 1107.5, 1108.8, 1107, 1106.4, 1106.5, 1109.6, 1108.9, 1109.7, 1109.4, 1110.9, 1112.2, 1114.1, 1113.5, 1113.5, 1115.9, 1117.3, 1115.2, 1114.5, 1114.9, 1112.7, 1113.2, 1114.2, 1114.9, 1119.6, 1118.8, 1119.6, 1122.1, 1123.1, 1122.6, 1120.7, 1120.5, 1121.4, 1121.3, 1122, 1122.3, 1121, 1121.5, 1120.4, 1119, 1118.4, 1119.7, 1117.9, 1118.9, 1119.8, 1119.4, 1117.6, 1117.2, 1117.5, 1118.2, 1117.3, 1128.3, 1126.4, 1125.7, 1125.3, 1122.8, 1120.6, 1121, 1122.3, 1121.1, 1120.3, 1118, 1118.5, 1119.3, 1118.2, 1118.9, 1122.1, 1120.3, 1120.8, 1114, 1115.9, 1116.5, 1116.1, 1115.8, 1115.9, 1114.3, 1115.6, 1114.6, 1114.8, 1116.3, 1114.9, 1112.7, 1115.7, 1114.6, 1115.5, 1113.4, 1111.7, 1113.4, 1112.8, 1112.1, 1115.4, 1113.5, 1112.4, 1118, 1117, 1117.1, 1116.6, 1116.5, 1117.9, 1118.4, 1117.8, 1118.4, 1120.4, 1121.4, 1122.5, 1122.3, 1122.3, 1121.8, 1122.9, 1122, 1122, 1123, 1121.8, 1123.9, 1122.9, 1126.4, 1126.3, 1126.7, 1127.2, 1127.6, 1128.8, 1129.7, 1128.6, 1128.6, 1129.5, 1127.6, 1127.4, 1126.1, 1125.8, 1125.8, 1125.9, 1126.1, 1126.4, 1125.8, 1125.2, 1124.8, 1125.4, 1127.4, 1128.9, 1128.3, 1125, 1126.3, 1128, 1128.3, 1130.1, 1129.6, 1127.9, 1127.6, 1128.4, 1128.7, 1127.8, 1127.1, 1128.5, 1128.5, 1124.9, 1126.8, 1128.2, 1130.4, 1128.6, 1130.2, 1126.7, 1132.5, 1138.2, 1138.6, 1140, 1144.2, 1138.9, 1142.8, 1143, 1142.6, 1143.5, 1141.8, 1141.3, 1141.2, 1141.8, 1143.5, 1143.9, 1142.4, 1145.4, 1146.4, 1147.6, 1145.8, 1148.2, 1153.5, 1155.3, 1152.1, 1154.6, 1155.9, 1155.5, 1156.4, 1156.4, 1156, 1156, 1156.1, 1154.8, 1156.4, 1156.1, 1155.7, 1155.3, 1154.8, 1154.8, 1156.3, 1157.9, 1159.4, 1159.4, 1159, 1151.5, 1149.9, 1154, 1155.3, 1157.6, 1157.9, 1162.8, 1174.5, 1174.1, 1174.1, 1165.3, 1168.5, 1165.4, 1165.5, 1166.2, 1166.7, 1166.2, 1166.4, 1165.8, 1168.5, 1173.8, 1176.4, 1175.9, 1182.5, 1182.1, 1192.1, 1193.6, 1194.4, 1195.6, 1201, 1195.5, 1190.7, 1189.6, 1191.5,
1193.2, 1193.9, 1194, 1193.2, 1193.1, 1191.8, 1193.4, 1186.7, 1188.7, 1189.5, 1189.3, 1191.7, 1196.6, 1198.5, 1189.7, 1195.5, 1195.6, 1197.3, 1195.2, 1190.8, 1187.9, 1189.4, 1189.6, 1192.1, 1193.4, 1191.5, 1191.3, 1191.8, 1191.8, 1191.2, 1188, 1187, 1182.3, 1182.6, 1182.8, 1183.7, 1187.9, 1191, 1192.6, 1193.3, 1192.1, 1192.5, 1194, 1196.9, 1197.4, 1197.4, 1199, 1208.7, 1208.4, 1207, 1206.1, 1209.3, 1206.7, 1208.2, 1207.6, 1217.6, 1217.6, 1224.8, 1237.3, 1235.9, 1236, 1233, 1247.1, 1254.5, 1248.4, 1249.4, 1245, 1245.1, 1247, 1240.7, 1238.6, 1236.3, 1238.2, 1233.9, 1233.5, 1239.3, 1245, 1242.6, 1239.5, 1238.4, 1242.6, 1238, 1238.7, 1236, 1239.5, 1238.4, 1237.8, 1236.9, 1239.3, 1238.7, 1238.5, 1238.5, 1233.8, 1228.1, 1223.7, 1224.7, 1221, 1220.6, 1219.8, 1219.5, 1212.4, 1210.1, 1209.5, 1210.2, 1209.9, 1209.6, 1211.7, 1210, 1205.7, 1207.4, 1209.4, 1208.4, 1208.4, 1204.7, 1198.4, 1193.4, 1194.2, 1197.9, 1201.3, 1196.2, 1200, 1211, 1212, 1215.4, 1213.9, 1215.3, 1211.2, 1216.4, 1213, 1209.1, 1204.2, 1204.2, 1200.4, 1200.9, 1203.2, 1198.2, 1202.6, 1203.7, 1209.3, 1209.1, 1206.8, 1207.3, 1211.5, 1204.6, 1202.9, 1203, 1202.3, 1207, 1209.4, 1210.9, 1210.6, 1212.8, 1210.2, 1210.3, 1208.9, 1208.3, 1209, 1207.4, 1209.3, 1209.1, 1210.5, 1210.1, 1209.5, 1209.9, 1208.1, 1207.5, 1207.6, 1206.8, 1203.4, 1204.3, 1205.8, 1206.9, 1210.8, 1215.8, 1218.8, 1227.8, 1232.9, 1234.7, 1237.5, 1231.3, 1231.6, 1232.8, 1227.2, 1227.5, 1228.4, 1228, 1226.7, 1226.5, 1224.4, 1224.2, 1221.5, 1222.9, 1230.8, 1231.7, 1230.7, 1229.3, 1231.6, 1233, 1231.3, 1231.9, 1232.7, 1229.6, 1226.6, 1226.1, 1225.9, 1223.5, 1223.3, 1217.1, 1216.3, 1217, 1217.7, 1211, 1209.5, 1206.6, 1205.2, 1204, 1207.6, 1209.1, 1212.6, 1212.2, 1210.3, 1211.1, 1209.2, 1208.2, 1207.9, 1208.9, 1209.3, 1211.2, 1215.8, 1215.7, 1221.1, 1220.5, 1216.6, 1216.7, 1217.8, 1216.9, 1219.2, 1218.8, 1217.4, 1219.3, 1218.6, 1221.6, 1225.6, 1224.6, 1223.8, 1222.8, 1223.6, 1226.1, 1226, 1231.1, 1230, 1225.9, 1228, 1228.6, 1228.7, 1228.1, 1226, 1224.2, 1226.2, 1230.6, 1237.1, 1238, 1236.1, 1244.4, 1250.2, 1248.6, 1245.6, 1238.4, 1239.7, 1230.5, 1230.3, 1229.4, 1225, 1228.5, 1236.3, 1233.3, 1234.4, 1233.4, 1234.5, 1237.2, 1241, 1239.5, 1237.4, 1236, 1233.3, 1236.5, 1234.8, 1236.4, 1239.2, 1239.8, 1242.1, 1235.1, 1239.1, 1233.6, 1233.7, 1234.5, 1237.5, 1239, 1237.6, 1236.5, 1238.1, 1240, 1239.6, 1237, 1231.4, 1233.1, 1233.4, 1236.6, 1237.1, 1229.3, 1227.6, 1217.5, 1219.2, 1220.4, 1222.3, 1226.2, 1224.9, 1222.8, 1221.9, 1221.8, 1226.4, 1226.4, 1225.2, 1226.8, 1229, 1227.3, 1230.8, 1234.1, 1235.1, 1234.9, 1229.9, 1231.3, 1229.2, 1234.6, 1232.4, 1233.8, 1232.6, 1234.6, 1239.6, 1240.9, 1239.3, 1241.1, 1241.4, 1247.2, 1244.8, 1244.4, 1245.7),
.Dim = c(1000L, 1L), index = structure(c(1451386800, 1451390400, 1451394000, 1451397600, 1451401200, 1451404800, 1451408400, 1451412000, 1451415600, 1451419200, 1451422800, 1451430000, 1451433600, 1451437200, 1451440800, 1451444400, 1451448000, 1451451600, 1451455200, 1451458800, 1451462400, 1451466000, 1451469600, 1451473200, 1451476800, 1451480400, 1451484000, 1451487600, 1451491200, 1451494800, 1451498400, 1451502000, 1451505600, 1451509200, 1451516400, 1451520000, 1451523600, 1451527200, 1451530800, 1451534400, 1451538000, 1451541600, 1451545200, 1451548800, 1451552400, 1451556000, 1451559600, 1451563200, 1451566800, 1451570400, 1451574000, 1451577600, 1451581200, 1451584800, 1451588400, 1451592000, 1451595600, 1451862000, 1451865600, 1451869200, 1451872800, 1451876400, 1451880000, 1451883600, 1451887200, 1451890800, 1451894400, 1451898000, 1451901600, 1451905200, 1451908800, 1451912400, 1451916000, 1451919600, 1451923200, 1451926800, 1451930400, 1451934000, 1451937600, 1451941200, 1451948400, 1451952000, 1451955600, 1451959200, 1451962800, 1451966400, 1451970000, 1451973600, 1451977200, 1451980800, 1451984400, 1451988000, 1451991600, 1451995200, 1451998800, 1452002400, 1452006000, 1452009600, 1452013200, 1452016800, 1452020400, 1452024000, 1452027600, 1452034800, 1452038400, 1452042000, 1452045600, 1452049200, 1452052800, 1452056400, 1452060000, 1452063600, 1452067200, 1452070800, 1452074400, 1452078000, 1452081600, 1452085200, 1452088800, 1452092400, 1452096000, 1452099600, 1452103200, 1452106800, 1452110400, 1452114000, 1452121200, 1452124800, 1452128400, 1452132000, 1452135600, 1452139200, 1452142800, 1452146400, 1452150000, 1452153600, 1452157200, 1452160800, 1452164400, 1452168000, 1452171600, 1452175200, 1452178800, 1452182400, 1452186000, 1452189600, 1452193200, 1452196800, 1452200400, 1452207600, 1452211200, 1452214800, 1452218400, 1452222000, 1452225600, 1452229200, 1452232800, 1452236400, 1452240000, 1452243600, 1452247200, 1452250800, 1452254400, 1452258000, 1452261600, 1452265200, 1452268800, 1452272400, 1452276000, 1452279600, 1452283200, 1452286800, 1452466800, 1452470400, 1452474000, 1452477600, 1452481200, 1452484800, 1452488400, 1452492000, 1452495600, 1452499200, 1452502800, 1452506400, 1452510000, 1452513600, 1452517200, 1452520800, 1452524400, 1452528000, 1452531600, 1452535200, 1452538800, 1452542400, 1452546000, 1452553200, 1452556800, 1452560400, 1452564000, 1452567600, 1452571200, 1452574800, 1452578400, 1452582000, 1452585600, 1452589200, 1452592800, 1452596400, 1452600000, 1452603600, 1452607200, 1452610800, 1452614400, 1452618000, 1452621600, 1452625200, 1452628800, 1452632400, 1452639600, 1452643200, 1452646800, 1452650400, 1452654000, 1452657600, 1452661200, 1452664800, 1452668400, 1452672000, 1452675600, 1452679200, 1452682800, 1452686400, 1452690000, 1452693600, 1452697200, 1452700800, 1452704400, 1452708000, 1452711600, 1452715200, 1452718800, 1452726000, 1452729600, 1452733200, 1452736800, 1452740400, 1452744000, 1452747600, 1452751200, 1452754800, 1452758400, 1452762000, 1452765600, 1452769200, 1452772800, 1452776400, 1452780000, 1452783600, 1452787200, 1452790800, 1452794400, 1452798000, 1452801600, 1452805200, 1452812400, 1452816000, 1452819600, 1452823200, 1452826800, 1452830400, 1452834000, 1452837600, 1452841200, 1452844800, 1452848400, 1452852000, 1452855600, 1452859200, 1452862800, 1452866400, 1452870000, 1452873600, 1452877200, 1452880800, 1452884400, 1452888000, 1452891600, 1453071600, 1453075200, 1453078800, 1453082400, 1453086000, 1453089600, 1453093200, 1453096800, 1453100400, 1453104000, 1453107600, 1453111200, 1453114800, 1453118400, 1453122000, 1453125600, 1453129200, 1453132800, 1453136400, 1453158000, 1453161600, 1453165200, 1453168800, 1453172400, 1453176000, 1453179600, 1453183200, 1453186800, 1453190400, 1453194000, 1453197600, 1453201200, 1453204800, 1453208400, 1453212000, 1453215600, 1453219200, 1453222800,
1453226400, 1453230000, 1453233600, 1453237200, 1453244400, 1453248000, 1453251600, 1453255200, 1453258800, 1453262400, 1453266000, 1453269600, 1453273200, 1453276800, 1453280400, 1453284000, 1453287600, 1453291200, 1453294800, 1453298400, 1453302000, 1453305600, 1453309200, 1453312800, 1453316400, 1453320000, 1453323600, 1453330800, 1453334400, 1453338000, 1453341600, 1453345200, 1453348800, 1453352400, 1453356000, 1453359600, 1453363200, 1453366800, 1453370400, 1453374000, 1453377600, 1453381200, 1453384800, 1453388400, 1453392000, 1453395600, 1453399200, 1453402800, 1453406400, 1453410000, 1453417200, 1453420800, 1453424400, 1453428000, 1453431600, 1453435200, 1453438800, 1453442400, 1453446000, 1453449600, 1453453200, 1453456800, 1453460400, 1453464000, 1453467600, 1453471200, 1453474800, 1453478400, 1453482000, 1453485600, 1453489200, 1453492800, 1453496400, 1453676400, 1453680000, 1453683600, 1453687200, 1453690800, 1453694400, 1453698000, 1453701600, 1453705200, 1453708800, 1453712400, 1453716000, 1453719600, 1453723200, 1453726800, 1453730400, 1453734000, 1453737600, 1453741200, 1453744800, 1453748400, 1453752000, 1453755600, 1453762800, 1453766400, 1453770000, 1453773600, 1453777200, 1453780800, 1453784400, 1453788000, 1453791600, 1453795200, 1453798800, 1453802400, 1453806000, 1453809600, 1453813200, 1453816800, 1453820400, 1453824000, 1453827600, 1453831200, 1453834800, 1453838400, 1453842000, 1453849200, 1453852800, 1453856400, 1453860000, 1453863600, 1453867200, 1453870800, 1453874400, 1453878000, 1453881600, 1453885200, 1453888800, 1453892400, 1453896000, 1453899600, 1453903200, 1453906800, 1453910400, 1453914000, 1453917600, 1453921200, 1453924800, 1453928400, 1453935600, 1453939200, 1453942800, 1453946400, 1453950000, 1453953600, 1453957200, 1453960800, 1453964400, 1453968000, 1453971600, 1453975200, 1453978800, 1453982400, 1453986000, 1453989600, 1453993200, 1453996800, 1454000400, 1454004000, 1454007600, 1454011200, 1454014800, 1454022000, 1454025600, 1454029200, 1454032800, 1454036400, 1454040000, 1454043600, 1454047200, 1454050800, 1454054400, 1454058000, 1454061600, 1454065200, 1454068800, 1454072400, 1454076000, 1454079600, 1454083200, 1454086800, 1454090400, 1454094000, 1454097600, 1454101200, 1454281200, 1454284800, 1454288400, 1454292000, 1454295600, 1454299200, 1454302800, 1454306400, 1454310000, 1454313600, 1454317200, 1454320800, 1454324400, 1454328000, 1454331600, 1454335200, 1454338800, 1454342400, 1454346000, 1454349600, 1454353200, 1454356800, 1454360400, 1454367600, 1454371200, 1454374800, 1454378400, 1454382000, 1454385600, 1454389200, 1454392800, 1454396400, 1454400000, 1454403600, 1454407200, 1454410800, 1454414400, 1454418000, 1454421600, 1454425200, 1454428800, 1454432400, 1454436000, 1454439600, 1454443200, 1454446800, 1454454000, 1454457600, 1454461200, 1454464800, 1454468400, 1454472000, 1454475600, 1454479200, 1454482800, 1454486400, 1454490000, 1454493600, 1454497200, 1454500800, 1454504400, 1454508000, 1454511600, 1454515200, 1454518800, 1454522400, 1454526000, 1454529600, 1454533200, 1454540400, 1454544000, 1454547600, 1454551200, 1454554800, 1454558400, 1454562000, 1454565600, 1454569200, 1454572800, 1454576400, 1454580000, 1454583600, 1454587200, 1454590800, 1454594400, 1454598000, 1454601600, 1454605200, 1454608800, 1454612400, 1454616000, 1454619600, 1454626800, 1454630400, 1454634000, 1454637600, 1454641200, 1454644800, 1454648400, 1454652000,
1454655600, 1454659200, 1454662800, 1454666400, 1454670000, 1454673600, 1454677200, 1454680800, 1454684400, 1454688000, 1454691600, 1454695200, 1454698800, 1454702400, 1454706000, 1454709600, 1454886000, 1454889600, 1454893200, 1454896800, 1454900400, 1454904000, 1454907600, 1454911200, 1454914800, 1454918400, 1454922000, 1454925600, 1454929200, 1454932800, 1454936400, 1454940000, 1454943600, 1454947200, 1454950800, 1454954400, 1454958000, 1454961600, 1454965200, 1454972400, 1454976000, 1454979600, 1454983200, 1454986800, 1454990400, 1454994000, 1454997600, 1455001200, 1455004800, 1455008400, 1455012000, 1455015600, 1455019200, 1455022800, 1455026400, 1455030000, 1455033600, 1455037200, 1455040800, 1455044400, 1455048000, 1455051600, 1455058800, 1455062400, 1455066000, 1455069600, 1455073200, 1455076800, 1455080400, 1455084000, 1455087600, 1455091200, 1455094800, 1455098400, 1455102000, 1455105600, 1455109200, 1455112800, 1455116400, 1455120000, 1455123600, 1455127200, 1455130800, 1455134400, 1455138000, 1455141600, 1455145200, 1455148800, 1455152400, 1455156000,
1455159600, 1455163200, 1455166800, 1455170400, 1455174000, 1455177600, 1455181200, 1455184800, 1455188400, 1455192000, 1455195600, 1455199200, 1455202800, 1455206400, 1455210000, 1455213600, 1455217200, 1455220800, 1455224400, 1455231600, 1455235200, 1455238800, 1455242400, 1455246000, 1455249600, 1455253200, 1455256800, 1455260400, 1455264000, 1455267600, 1455271200, 1455274800, 1455278400, 1455282000, 1455285600, 1455289200, 1455292800, 1455296400, 1455300000, 1455303600, 1455307200, 1455310800, 1455490800, 1455494400, 1455498000, 1455501600, 1455505200, 1455508800, 1455512400, 1455516000, 1455519600, 1455523200, 1455526800, 1455530400, 1455534000, 1455537600, 1455541200, 1455544800, 1455548400, 1455552000, 1455555600, 1455577200, 1455580800, 1455584400, 1455588000, 1455591600, 1455595200, 1455598800, 1455602400, 1455606000, 1455609600, 1455613200, 1455616800, 1455620400, 1455624000, 1455627600, 1455631200, 1455634800, 1455638400, 1455642000, 1455645600, 1455649200, 1455652800, 1455656400, 1455663600, 1455667200, 1455670800, 1455674400, 1455678000, 1455681600, 1455685200, 1455688800, 1455692400, 1455696000, 1455699600, 1455703200, 1455706800, 1455710400, 1455714000, 1455717600, 1455721200, 1455724800, 1455728400, 1455732000, 1455735600, 1455739200, 1455742800, 1455750000, 1455753600, 1455757200, 1455760800, 1455764400, 1455768000, 1455771600, 1455775200, 1455778800, 1455782400, 1455786000, 1455789600, 1455793200, 1455796800, 1455800400, 1455804000, 1455807600, 1455811200, 1455814800, 1455818400, 1455822000, 1455825600, 1455829200, 1455836400, 1455840000, 1455843600, 1455847200, 1455850800, 1455854400, 1455858000, 1455861600, 1455865200, 1455868800, 1455872400, 1455876000, 1455879600, 1455883200, 1455886800, 1455890400, 1455894000, 1455897600, 1455901200, 1455904800, 1455908400, 1455912000, 1455915600, 1456095600, 1456099200, 1456102800, 1456106400, 1456110000, 1456113600, 1456117200, 1456120800, 1456124400, 1456128000, 1456131600, 1456135200, 1456138800, 1456142400, 1456146000, 1456149600, 1456153200, 1456156800, 1456160400, 1456164000, 1456167600, 1456171200, 1456174800, 1456182000, 1456185600, 1456189200, 1456192800, 1456196400, 1456200000, 1456203600, 1456207200, 1456210800, 1456214400, 1456218000, 1456221600, 1456225200, 1456228800, 1456232400, 1456236000, 1456239600, 1456243200, 1456246800, 1456250400, 1456254000, 1456257600, 1456261200, 1456268400, 1456272000, 1456275600, 1456279200, 1456282800, 1456286400, 1456290000, 1456293600, 1456297200, 1456300800, 1456304400, 1456308000, 1456311600, 1456315200, 1456318800, 1456322400, 1456326000, 1456329600, 1456333200, 1456336800, 1456340400, 1456344000, 1456347600, 1456354800, 1456358400, 1456362000, 1456365600, 1456369200, 1456372800, 1456376400, 1456380000, 1456383600, 1456387200, 1456390800, 1456394400, 1456398000, 1456401600, 1456405200, 1456408800, 1456412400, 1456416000, 1456419600, 1456423200, 1456426800, 1456430400, 1456434000, 1456441200, 1456444800, 1456448400, 1456452000, 1456455600, 1456459200, 1456462800, 1456466400, 1456470000, 1456473600, 1456477200, 1456480800, 1456484400, 1456488000, 1456491600, 1456495200, 1456498800, 1456502400, 1456506000, 1456509600, 1456513200, 1456516800, 1456520400, 1456700400, 1456704000, 1456707600, 1456711200, 1456714800, 1456718400, 1456722000, 1456725600, 1456729200, 1456732800, 1456736400, 1456740000, 1456743600, 1456747200, 1456750800, 1456754400, 1456758000, 1456761600, 1456765200, 1456768800, 1456772400, 1456776000, 1456779600, 1456786800, 1456790400, 1456794000, 1456797600, 1456801200, 1456804800),
tzone = "", tclass = c("POSIXlt","POSIXt")), class = c("xts", "zoo"), .indexCLASS = c("POSIXlt", "POSIXt"), tclass = c("POSIXlt", "POSIXt"), .indexTZ = "", tzone = "", .CLASS = "double")
#get 1st Friday of every Month
NFPFri <- DATSxts[.indexmday(DATSxts) >= 1 & .indexmday(DATSxts) <= 7 &.indexwday(DATSxts) == 5] #1st Friday of every Month
#get following Monday => if 1st Friday is days 1:4 then 1st Monday, otherwise 2nd Monday
ifelse (.indexwday(NFPFri) >=1 & .indexwday(NFPFri) <= 4 ,
PostNFPMon <- DATSxts[.indexmday(DATSxts) >= 4 & .indexmday(DATSxts) <= 7 &.indexwday(DATSxts) == 1],
PostNFPMon <- DATSxts[.indexmday(DATSxts) >= 8 & .indexmday(DATSxts) <= 10 &.indexwday(DATSxts) == 1])
#merge Friday and Monday, put into one column, and eliminate NA's
NFP <- merge(NFPFri, PostNFPMon)
NFP <- rowSums(NFP,na.rm = TRUE)
代码提供了一个名为NFP的子集，其中包含这两天的所有价格。但它有一个问题：使用rowSums会导致NFP没有DateTime索引。
ifelse，merge和rowSums似乎
非常低效）****（注意：由于某些奇怪的原因，如果我将所有数据/ xts代码放在少于8行的数据中，则加载数据会产生错误消息）****
编辑：将cbind替换为merge以保留列名称。
答案 0 :(得分：2)
BLS网站已经列出了最近和即将到来的日期http://www.bls.gov/schedule/news_release/empsit.htm：
Reference Month Release Date Release Time
October 2015 Nov. 06, 2015 08:30 AM
November 2015 Dec. 04, 2015 08:30 AM
December 2015 Jan. 08, 2016 08:30 AM
January 2016 Feb. 05, 2016 08:30 AM
February 2016 Mar. 04, 2016 08:30 AM
March 2016 Apr. 01, 2016 08:30 AM
April 2016 May 06, 2016 08:30 AM
May 2016 Jun. 03, 2016 08:30 AM
June 2016 Jul. 08, 2016 08:30 AM
July 2016 Aug. 05, 2016 08:30 AM
August 2016 Sep. 02, 2016 08:30 AM
September 2016 Oct. 07, 2016 08:30 AM
October 2016 Nov. 04, 2016 08:30 AM
November 2016 Dec. 02, 2016 08:30 AM
注意这不是＆＃34;第一个星期五＆＃34;的两个项目。 Dirk在周五引用的帖子中提出的方法将通过以下方式实施：
library(RcppBDT)
for( y in 2015:2016){ for(m in 1:12){print( getNthDayOfWeek(first, Fri, m, y))}}
[1] "2015-01-02"
[1] "2015-02-06"
[1] "2015-03-06"
[1] "2015-04-03"
[1] "2015-05-01"
[1] "2015-06-05"
[1] "2015-07-03"
[1] "2015-08-07"
[1] "2015-09-04"
[1] "2015-10-02"
[1] "2015-11-06"
[1] "2015-12-04"
[1] "2016-01-01"
[1] "2016-02-05"
[1] "2016-03-04"
[1] "2016-04-01"
[1] "2016-05-06"
[1] "2016-06-03"
[1] "2016-07-01"
[1] "2016-08-05"
[1] "2016-09-02"
[1] "2016-10-07"
[1] "2016-11-04"
[1] "2016-12-02"
对于星期五：下周一请求，只是这个添加的设备：
i=-1; for( y in 2015:2016){ for(m in 1:12){
i=i+2;
x[i] <- getNthDayOfWeek(first, Fri, m, y)
x[i+1] <- x[1] + 3 }}
#---------
x
[1] "2015-01-02" "2015-01-05" "2015-02-06" "2015-01-05" "2015-03-06" "2015-01-05"
[7] "2015-04-03" "2015-01-05" "2015-05-01" "2015-01-05" "2015-06-05" "2015-01-05"
[13] "2015-07-03" "2015-01-05" "2015-08-07" "2015-01-05" "2015-09-04" "2015-01-05"
[19] "2015-10-02" "2015-01-05" "2015-11-06" "2015-01-05" "2015-12-04" "2015-01-05"
[25] "2016-01-01" "2015-01-05" "2016-02-05" "2015-01-05" "2016-03-04" "2015-01-05"
[31] "2016-04-01" "2015-01-05" "2016-05-06" "2015-01-05" "2016-06-03" "2015-01-05"
[37] "2016-07-01" "2015-01-05" "2016-08-05" "2015-01-05" "2016-09-02" "2015-01-05"
[43] "2016-10-07" "2015-01-05" "2016-11-04" "2015-01-05" "2016-12-02" "2015-01-05"
注意：我在使用R 3.3.0和新gfortran编译器的Mac上，但这似乎仍然只是工作＆＃34;。
答案 1 :(得分：0)
感谢@hvollmeier回答这个问题：Excel or R: Merge time series with missing values。不得不将rowSums的结果保存在NFP $ FriAndMon而不仅仅是NFP。现在保留DateTime索引。
NFP <- merge(NFPFri, PostNFPMon)
NFP$FriAndMon <- rowSums(result,na.rm = TRUE)
NFP <- NFP[,3]